Riferimenti:
isola_aggiunta
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/adjunct_island')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
anaphor_gender_agreement
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/anaphor_gender_agreement')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
anaphor_number_agreement
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/anaphor_number_agreement')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
animato_soggetto_passivo
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/animate_subject_passive')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
anima_soggetto_trans
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/animate_subject_trans')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
causale
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/causative')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
complesso_NP_isola
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/complex_NP_island')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
coordina_struttura_vincolo_complesso_ramo_sinistro
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/coordinate_structure_constraint_complex_left_branch')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
coordina_struttura_vincolo_oggetto_estrazione
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/coordinate_structure_constraint_object_extraction')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
determinante_sostantivo_accordo_1
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_1')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
determinante_sostantivo_accordo_2
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_2')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
determinante_sostantivo_accordo_irregolare_1
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_irregular_1')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
determinante_sostantivo_accordo_irregolare_2
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_irregular_2')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
determinante_sostantivo_accordo_con_agg_2
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_with_adj_2')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
determinante_sostantivo_accordo_con_adj_irregolare_1
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_with_adj_irregular_1')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
determinante_sostantivo_accordo_con_adj_irregolare_2
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_with_adj_irregular_2')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
determinante_sostantivo_accordo_con_aggettivo_1
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_with_adjective_1')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
distrattore_accordo_relazionale_sostantivo
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/distractor_agreement_relational_noun')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
distrattore_agreement_relative_clause
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/distractor_agreement_relative_clause')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
drop_argomento
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/drop_argument')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
puntini di sospensione_n_bar_1
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/ellipsis_n_bar_1')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
puntini di sospensione_n_bar_2
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/ellipsis_n_bar_2')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
esistenziale_lì_oggetto_raising
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/existential_there_object_raising')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
esistenziale_ci_quantificatori_1
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/existential_there_quantifiers_1')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
esistenziale_ci_quantificatori_2
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/existential_there_quantifiers_2')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
esistenziale_là_soggetto_sollevamento
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/existential_there_subject_raising')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
imprecazione_it_object_raising
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/expletive_it_object_raising')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
incoativo
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/inchoative')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
intransitivo
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/intransitive')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
aggettivi_participio_passato_irregolari
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/irregular_past_participle_adjectives')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
verbi_participi_passati_irregolari
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/irregular_past_participle_verbs')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
irregolare_plural_subject_verb_agreement_1
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/irregular_plural_subject_verb_agreement_1')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
irregolare_plural_subject_verb_agreement_2
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/irregular_plural_subject_verb_agreement_2')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
left_branch_island_echo_question
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/left_branch_island_echo_question')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
left_branch_island_simple_question
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/left_branch_island_simple_question')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
matrice_question_npi_licensor_present
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/matrix_question_npi_licensor_present')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
npi_present_1
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/npi_present_1')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
npi_present_2
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/npi_present_2')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
only_npi_licensor_present
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/only_npi_licensor_present')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
only_npi_scope
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/only_npi_scope')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
passivo_1
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/passive_1')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
passivo_2
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/passive_2')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
principio_A_c_comando
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/principle_A_c_command')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
principio_A_caso_1
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/principle_A_case_1')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
principio_A_caso_2
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/principle_A_case_2')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
principio_A_dominio_1
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/principle_A_domain_1')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
principio_A_dominio_2
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/principle_A_domain_2')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
principio_A_dominio_3
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/principle_A_domain_3')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
principio_A_ricostruzione
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/principle_A_reconstruction')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
normal_plural_subject_verb_agreement_1
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/regular_plural_subject_verb_agreement_1')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
normal_plural_subject_verb_agreement_2
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/regular_plural_subject_verb_agreement_2')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
sentential_negation_npi_licensor_present
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/sentential_negation_npi_licensor_present')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
sentential_negation_npi_scope
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/sentential_negation_npi_scope')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
sentential_subject_island
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/sentential_subject_island')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
quantificatori_superlativi_1
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/superlative_quantifiers_1')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
quantificatori_superlativi_2
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/superlative_quantifiers_2')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
duro_vs_raising_1
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/tough_vs_raising_1')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
duro_vs_raising_2
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/tough_vs_raising_2')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
transitivo
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/transitive')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
whi_island
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/wh_island')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_questions_object_gap
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/wh_questions_object_gap')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_questions_subject_gap
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/wh_questions_subject_gap')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_questions_subject_gap_long_distance
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/wh_questions_subject_gap_long_distance')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_vs_that_no_gap
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/wh_vs_that_no_gap')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_vs_that_no_gap_long_distance
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/wh_vs_that_no_gap_long_distance')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_vs_that_with_gap
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/wh_vs_that_with_gap')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_vs_that_with_gap_long_distance
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:blimp/wh_vs_that_with_gap_long_distance')
- Descrizione :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- Licenza : nessuna licenza conosciuta
- Versione : 0.1.0
- Divide :
Diviso | Esempi |
---|---|
'train' | 1000 |
- Caratteristiche :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}