Referensi:
anggapan_semua_n_anggapan
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:imppres/presupposition_all_n_presupposition')
- Keterangan :
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.
- Lisensi : Lisensi Publik Internasional Creative Commons Attribution-NonCommercial 4.0
- Versi : 1.1.0
- Perpecahan :
Membelah | Contoh |
---|---|
'all_n_presupposition' | 1900 |
- Fitur :
{
"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"
}
}
praanggapan_kedua_praanggapan
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:imppres/presupposition_both_presupposition')
- Keterangan :
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.
- Lisensi : Lisensi Publik Internasional Creative Commons Attribution-NonCommercial 4.0
- Versi : 1.1.0
- Perpecahan :
Membelah | Contoh |
---|---|
'both_presupposition' | 1900 |
- Fitur :
{
"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"
}
}
anggapan_perubahan_kondisi_keadaan
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:imppres/presupposition_change_of_state')
- Keterangan :
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.
- Lisensi : Lisensi Publik Internasional Creative Commons Attribution-NonCommercial 4.0
- Versi : 1.1.0
- Perpecahan :
Membelah | Contoh |
---|---|
'change_of_state' | 1900 |
- Fitur :
{
"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"
}
}
anggapan_celah_keberadaan
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:imppres/presupposition_cleft_existence')
- Keterangan :
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.
- Lisensi : Lisensi Publik Internasional Creative Commons Attribution-NonCommercial 4.0
- Versi : 1.1.0
- Perpecahan :
Membelah | Contoh |
---|---|
'cleft_existence' | 1900 |
- Fitur :
{
"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"
}
}
anggapan_celah_keunikan
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:imppres/presupposition_cleft_uniqueness')
- Keterangan :
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.
- Lisensi : Lisensi Publik Internasional Creative Commons Attribution-NonCommercial 4.0
- Versi : 1.1.0
- Perpecahan :
Membelah | Contoh |
---|---|
'cleft_uniqueness' | 1900 |
- Fitur :
{
"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"
}
}
prasangka_hanya_presupposisi
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:imppres/presupposition_only_presupposition')
- Keterangan :
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.
- Lisensi : Lisensi Publik Internasional Creative Commons Attribution-NonCommercial 4.0
- Versi : 1.1.0
- Perpecahan :
Membelah | Contoh |
---|---|
'only_presupposition' | 1900 |
- Fitur :
{
"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"
}
}
anggapan_kepemilikan_keberadaan_yang terbatas
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:imppres/presupposition_possessed_definites_existence')
- Keterangan :
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.
- Lisensi : Lisensi Publik Internasional Creative Commons Attribution-NonCommercial 4.0
- Versi : 1.1.0
- Perpecahan :
Membelah | Contoh |
---|---|
'possessed_definites_existence' | 1900 |
- Fitur :
{
"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"
}
}
anggapan_kepemilikan_kepastian_keunikan
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:imppres/presupposition_possessed_definites_uniqueness')
- Keterangan :
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.
- Lisensi : Lisensi Publik Internasional Creative Commons Attribution-NonCommercial 4.0
- Versi : 1.1.0
- Perpecahan :
Membelah | Contoh |
---|---|
'possessed_definites_uniqueness' | 1900 |
- Fitur :
{
"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"
}
}
anggapan_pertanyaan_anggapan
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:imppres/presupposition_question_presupposition')
- Keterangan :
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.
- Lisensi : Lisensi Publik Internasional Creative Commons Attribution-NonCommercial 4.0
- Versi : 1.1.0
- Perpecahan :
Membelah | Contoh |
---|---|
'question_presupposition' | 1900 |
- Fitur :
{
"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"
}
}
implikatur_konektif
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:imppres/implicature_connectives')
- Keterangan :
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.
- Lisensi : Lisensi Publik Internasional Creative Commons Attribution-NonCommercial 4.0
- Versi : 1.1.0
- Perpecahan :
Membelah | Contoh |
---|---|
'connectives' | 1200 |
- Fitur :
{
"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"
}
}
implikatur_kata sifat_gradable
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:imppres/implicature_gradable_adjective')
- Keterangan :
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.
- Lisensi : Lisensi Publik Internasional Creative Commons Attribution-NonCommercial 4.0
- Versi : 1.1.0
- Perpecahan :
Membelah | Contoh |
---|---|
'gradable_adjective' | 1200 |
- Fitur :
{
"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"
}
}
implikatur_gradable_verb
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:imppres/implicature_gradable_verb')
- Keterangan :
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.
- Lisensi : Lisensi Publik Internasional Creative Commons Attribution-NonCommercial 4.0
- Versi : 1.1.0
- Perpecahan :
Membelah | Contoh |
---|---|
'gradable_verb' | 1200 |
- Fitur :
{
"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"
}
}
implikatur_modals
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:imppres/implicature_modals')
- Keterangan :
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.
- Lisensi : Lisensi Publik Internasional Creative Commons Attribution-NonCommercial 4.0
- Versi : 1.1.0
- Perpecahan :
Membelah | Contoh |
---|---|
'modals' | 1200 |
- Fitur :
{
"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"
}
}
implikatur_angka_10_100
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:imppres/implicature_numerals_10_100')
- Keterangan :
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.
- Lisensi : Lisensi Publik Internasional Creative Commons Attribution-NonCommercial 4.0
- Versi : 1.1.0
- Perpecahan :
Membelah | Contoh |
---|---|
'numerals_10_100' | 1200 |
- Fitur :
{
"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"
}
}
implikatur_angka_2_3
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:imppres/implicature_numerals_2_3')
- Keterangan :
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.
- Lisensi : Lisensi Publik Internasional Creative Commons Attribution-NonCommercial 4.0
- Versi : 1.1.0
- Perpecahan :
Membelah | Contoh |
---|---|
'numerals_2_3' | 1200 |
- Fitur :
{
"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"
}
}
implikatur_quantifier
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:imppres/implicature_quantifiers')
- Keterangan :
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.
- Lisensi : Lisensi Publik Internasional Creative Commons Attribution-NonCommercial 4.0
- Versi : 1.1.0
- Perpecahan :
Membelah | Contoh |
---|---|
'quantifiers' | 1200 |
- Fitur :
{
"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"
}
}