مراجع:
presupposition_all_n_presupposition
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:imppres/presupposition_all_n_presupposition')
- وصف :
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.
- الترخيص : إسناد المشاع الإبداعي - غير تجاري 4.0 الرخصة العامة الدولية
- الإصدار : 1.1.0
- الإنشقاقات :
ينقسم | أمثلة |
---|---|
'all_n_presupposition' | 1900 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:imppres/presupposition_both_presupposition')
- وصف :
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.
- الترخيص : إسناد المشاع الإبداعي - غير تجاري 4.0 الرخصة العامة الدولية
- الإصدار : 1.1.0
- الإنشقاقات :
ينقسم | أمثلة |
---|---|
'both_presupposition' | 1900 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:imppres/presupposition_change_of_state')
- وصف :
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.
- الترخيص : إسناد المشاع الإبداعي - غير تجاري 4.0 الرخصة العامة الدولية
- الإصدار : 1.1.0
- الإنشقاقات :
ينقسم | أمثلة |
---|---|
'change_of_state' | 1900 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:imppres/presupposition_cleft_existence')
- وصف :
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.
- الترخيص : إسناد المشاع الإبداعي - غير تجاري 4.0 الرخصة العامة الدولية
- الإصدار : 1.1.0
- الإنشقاقات :
ينقسم | أمثلة |
---|---|
'cleft_existence' | 1900 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:imppres/presupposition_cleft_uniqueness')
- وصف :
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.
- الترخيص : إسناد المشاع الإبداعي - غير تجاري 4.0 الرخصة العامة الدولية
- الإصدار : 1.1.0
- الإنشقاقات :
ينقسم | أمثلة |
---|---|
'cleft_uniqueness' | 1900 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:imppres/presupposition_only_presupposition')
- وصف :
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.
- الترخيص : إسناد المشاع الإبداعي - غير تجاري 4.0 الرخصة العامة الدولية
- الإصدار : 1.1.0
- الإنشقاقات :
ينقسم | أمثلة |
---|---|
'only_presupposition' | 1900 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:imppres/presupposition_possessed_definites_existence')
- وصف :
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.
- الترخيص : إسناد المشاع الإبداعي - غير تجاري 4.0 الرخصة العامة الدولية
- الإصدار : 1.1.0
- الإنشقاقات :
ينقسم | أمثلة |
---|---|
'possessed_definites_existence' | 1900 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:imppres/presupposition_possessed_definites_uniqueness')
- وصف :
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.
- الترخيص : إسناد المشاع الإبداعي - غير تجاري 4.0 الرخصة العامة الدولية
- الإصدار : 1.1.0
- الإنشقاقات :
ينقسم | أمثلة |
---|---|
'possessed_definites_uniqueness' | 1900 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:imppres/presupposition_question_presupposition')
- وصف :
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.
- الترخيص : إسناد المشاع الإبداعي - غير تجاري 4.0 الرخصة العامة الدولية
- الإصدار : 1.1.0
- الإنشقاقات :
ينقسم | أمثلة |
---|---|
'question_presupposition' | 1900 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:imppres/implicature_connectives')
- وصف :
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.
- الترخيص : إسناد المشاع الإبداعي - غير تجاري 4.0 الرخصة العامة الدولية
- الإصدار : 1.1.0
- الإنشقاقات :
ينقسم | أمثلة |
---|---|
'connectives' | 1200 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:imppres/implicature_gradable_adjective')
- وصف :
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.
- الترخيص : إسناد المشاع الإبداعي - غير تجاري 4.0 الرخصة العامة الدولية
- الإصدار : 1.1.0
- الإنشقاقات :
ينقسم | أمثلة |
---|---|
'gradable_adjective' | 1200 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:imppres/implicature_gradable_verb')
- وصف :
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.
- الترخيص : إسناد المشاع الإبداعي - غير تجاري 4.0 الرخصة العامة الدولية
- الإصدار : 1.1.0
- الإنشقاقات :
ينقسم | أمثلة |
---|---|
'gradable_verb' | 1200 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:imppres/implicature_modals')
- وصف :
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.
- الترخيص : إسناد المشاع الإبداعي - غير تجاري 4.0 الرخصة العامة الدولية
- الإصدار : 1.1.0
- الإنشقاقات :
ينقسم | أمثلة |
---|---|
'modals' | 1200 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:imppres/implicature_numerals_10_100')
- وصف :
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.
- الترخيص : إسناد المشاع الإبداعي - غير تجاري 4.0 الرخصة العامة الدولية
- الإصدار : 1.1.0
- الإنشقاقات :
ينقسم | أمثلة |
---|---|
'numerals_10_100' | 1200 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:imppres/implicature_numerals_2_3')
- وصف :
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.
- الترخيص : إسناد المشاع الإبداعي - غير تجاري 4.0 الرخصة العامة الدولية
- الإصدار : 1.1.0
- الإنشقاقات :
ينقسم | أمثلة |
---|---|
'numerals_2_3' | 1200 |
- سمات :
{
"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
استخدم الأمر التالي لتحميل مجموعة البيانات هذه في TFDS:
ds = tfds.load('huggingface:imppres/implicature_quantifiers')
- وصف :
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.
- الترخيص : إسناد المشاع الإبداعي - غير تجاري 4.0 الرخصة العامة الدولية
- الإصدار : 1.1.0
- الإنشقاقات :
ينقسم | أمثلة |
---|---|
'quantifiers' | 1200 |
- سمات :
{
"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"
}
}