References:
presupposition_all_n_presupposition
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:imppres/presupposition_all_n_presupposition')
- Description:
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- License: Creative Commons Attribution-NonCommercial 4.0 International Public License
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'all_n_presupposition' |
1900 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"presupposition": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"pairID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"paradigmID": {
"dtype": "int16",
"id": null,
"_type": "Value"
}
}
presupposition_both_presupposition
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:imppres/presupposition_both_presupposition')
- Description:
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- License: Creative Commons Attribution-NonCommercial 4.0 International Public License
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'both_presupposition' |
1900 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"presupposition": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"pairID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"paradigmID": {
"dtype": "int16",
"id": null,
"_type": "Value"
}
}
presupposition_change_of_state
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:imppres/presupposition_change_of_state')
- Description:
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- License: Creative Commons Attribution-NonCommercial 4.0 International Public License
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'change_of_state' |
1900 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"presupposition": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"pairID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"paradigmID": {
"dtype": "int16",
"id": null,
"_type": "Value"
}
}
presupposition_cleft_existence
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:imppres/presupposition_cleft_existence')
- Description:
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- License: Creative Commons Attribution-NonCommercial 4.0 International Public License
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'cleft_existence' |
1900 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"presupposition": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"pairID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"paradigmID": {
"dtype": "int16",
"id": null,
"_type": "Value"
}
}
presupposition_cleft_uniqueness
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:imppres/presupposition_cleft_uniqueness')
- Description:
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- License: Creative Commons Attribution-NonCommercial 4.0 International Public License
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'cleft_uniqueness' |
1900 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"presupposition": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"pairID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"paradigmID": {
"dtype": "int16",
"id": null,
"_type": "Value"
}
}
presupposition_only_presupposition
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:imppres/presupposition_only_presupposition')
- Description:
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- License: Creative Commons Attribution-NonCommercial 4.0 International Public License
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'only_presupposition' |
1900 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"presupposition": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"pairID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"paradigmID": {
"dtype": "int16",
"id": null,
"_type": "Value"
}
}
presupposition_possessed_definites_existence
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:imppres/presupposition_possessed_definites_existence')
- Description:
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- License: Creative Commons Attribution-NonCommercial 4.0 International Public License
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'possessed_definites_existence' |
1900 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"presupposition": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"pairID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"paradigmID": {
"dtype": "int16",
"id": null,
"_type": "Value"
}
}
presupposition_possessed_definites_uniqueness
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:imppres/presupposition_possessed_definites_uniqueness')
- Description:
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- License: Creative Commons Attribution-NonCommercial 4.0 International Public License
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'possessed_definites_uniqueness' |
1900 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"presupposition": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"pairID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"paradigmID": {
"dtype": "int16",
"id": null,
"_type": "Value"
}
}
presupposition_question_presupposition
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:imppres/presupposition_question_presupposition')
- Description:
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- License: Creative Commons Attribution-NonCommercial 4.0 International Public License
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'question_presupposition' |
1900 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"presupposition": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"pairID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"paradigmID": {
"dtype": "int16",
"id": null,
"_type": "Value"
}
}
implicature_connectives
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:imppres/implicature_connectives')
- Description:
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- License: Creative Commons Attribution-NonCommercial 4.0 International Public License
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'connectives' |
1200 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label_log": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"gold_label_prag": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"spec_relation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"item_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lexemes": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
implicature_gradable_adjective
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:imppres/implicature_gradable_adjective')
- Description:
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- License: Creative Commons Attribution-NonCommercial 4.0 International Public License
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'gradable_adjective' |
1200 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label_log": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"gold_label_prag": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"spec_relation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"item_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lexemes": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
implicature_gradable_verb
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:imppres/implicature_gradable_verb')
- Description:
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- License: Creative Commons Attribution-NonCommercial 4.0 International Public License
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'gradable_verb' |
1200 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label_log": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"gold_label_prag": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"spec_relation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"item_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lexemes": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
implicature_modals
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:imppres/implicature_modals')
- Description:
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- License: Creative Commons Attribution-NonCommercial 4.0 International Public License
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'modals' |
1200 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label_log": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"gold_label_prag": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"spec_relation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"item_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lexemes": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
implicature_numerals_10_100
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:imppres/implicature_numerals_10_100')
- Description:
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- License: Creative Commons Attribution-NonCommercial 4.0 International Public License
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'numerals_10_100' |
1200 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label_log": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"gold_label_prag": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"spec_relation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"item_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lexemes": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
implicature_numerals_2_3
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:imppres/implicature_numerals_2_3')
- Description:
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- License: Creative Commons Attribution-NonCommercial 4.0 International Public License
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'numerals_2_3' |
1200 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label_log": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"gold_label_prag": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"spec_relation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"item_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lexemes": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
implicature_quantifiers
Use the following command to load this dataset in TFDS:
ds = tfds.load('huggingface:imppres/implicature_quantifiers')
- Description:
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al., 2015), MultiNLI (Williams et al., 2018) and XNLI (Conneau et al., 2018), which was created to evaluate how well trained NLI models recognize several classes of presuppositions and scalar implicatures.
- License: Creative Commons Attribution-NonCommercial 4.0 International Public License
- Version: 1.1.0
- Splits:
| Split | Examples |
|---|---|
'quantifiers' |
1200 |
- Features:
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"gold_label_log": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"gold_label_prag": {
"num_classes": 3,
"names": [
"entailment",
"neutral",
"contradiction"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"spec_relation": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"item_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"trigger": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lexemes": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}