सन्दर्भ:
वेबएनएलजी_चैलेंज_2017
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:web_nlg/webnlg_challenge_2017')
- विवरण :
The WebNLG challenge consists in mapping data to text. The training data consists
of Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation
of these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).
a. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)
b. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot
As the example illustrates, the task involves specific NLG subtasks such as sentence segmentation
(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),
aggregation (how to avoid repetitions) and surface realisation
(how to build a syntactically correct and natural sounding text).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 0.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'dev' | 872 |
'test' | 4615 |
'train' | 6940 |
- विशेषताएँ :
{
"category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"size": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"eid": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"original_triple_sets": {
"feature": {
"otriple_set": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"modified_triple_sets": {
"feature": {
"mtriple_set": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"shape": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"shape_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lex": {
"feature": {
"comment": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lid": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"test_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"dbpedia_links": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"links": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
रिलीज़_v1
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:web_nlg/release_v1')
- विवरण :
The WebNLG challenge consists in mapping data to text. The training data consists
of Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation
of these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).
a. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)
b. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot
As the example illustrates, the task involves specific NLG subtasks such as sentence segmentation
(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),
aggregation (how to avoid repetitions) and surface realisation
(how to build a syntactically correct and natural sounding text).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 0.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'full' | 14237 |
- विशेषताएँ :
{
"category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"size": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"eid": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"original_triple_sets": {
"feature": {
"otriple_set": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"modified_triple_sets": {
"feature": {
"mtriple_set": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"shape": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"shape_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lex": {
"feature": {
"comment": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lid": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"test_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"dbpedia_links": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"links": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
रिलीज़_v2
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:web_nlg/release_v2')
- विवरण :
The WebNLG challenge consists in mapping data to text. The training data consists
of Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation
of these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).
a. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)
b. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot
As the example illustrates, the task involves specific NLG subtasks such as sentence segmentation
(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),
aggregation (how to avoid repetitions) and surface realisation
(how to build a syntactically correct and natural sounding text).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 0.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'dev' | 1619 |
'test' | 1600 |
'train' | 12876 |
- विशेषताएँ :
{
"category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"size": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"eid": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"original_triple_sets": {
"feature": {
"otriple_set": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"modified_triple_sets": {
"feature": {
"mtriple_set": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"shape": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"shape_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lex": {
"feature": {
"comment": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lid": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"test_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"dbpedia_links": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"links": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
रिलीज़_v2_विवश
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:web_nlg/release_v2_constrained')
- विवरण :
The WebNLG challenge consists in mapping data to text. The training data consists
of Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation
of these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).
a. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)
b. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot
As the example illustrates, the task involves specific NLG subtasks such as sentence segmentation
(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),
aggregation (how to avoid repetitions) and surface realisation
(how to build a syntactically correct and natural sounding text).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 0.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'dev' | 1594 |
'test' | 1606 |
'train' | 12895 |
- विशेषताएँ :
{
"category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"size": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"eid": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"original_triple_sets": {
"feature": {
"otriple_set": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"modified_triple_sets": {
"feature": {
"mtriple_set": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"shape": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"shape_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lex": {
"feature": {
"comment": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lid": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"test_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"dbpedia_links": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"links": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
रिलीज़_v2.1
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:web_nlg/release_v2.1')
- विवरण :
The WebNLG challenge consists in mapping data to text. The training data consists
of Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation
of these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).
a. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)
b. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot
As the example illustrates, the task involves specific NLG subtasks such as sentence segmentation
(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),
aggregation (how to avoid repetitions) and surface realisation
(how to build a syntactically correct and natural sounding text).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 0.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'dev' | 1619 |
'test' | 1600 |
'train' | 12876 |
- विशेषताएँ :
{
"category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"size": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"eid": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"original_triple_sets": {
"feature": {
"otriple_set": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"modified_triple_sets": {
"feature": {
"mtriple_set": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"shape": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"shape_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lex": {
"feature": {
"comment": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lid": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"test_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"dbpedia_links": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"links": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
रिलीज़_v2.1_विवश
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:web_nlg/release_v2.1_constrained')
- विवरण :
The WebNLG challenge consists in mapping data to text. The training data consists
of Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation
of these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).
a. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)
b. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot
As the example illustrates, the task involves specific NLG subtasks such as sentence segmentation
(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),
aggregation (how to avoid repetitions) and surface realisation
(how to build a syntactically correct and natural sounding text).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 0.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'dev' | 1594 |
'test' | 1606 |
'train' | 12895 |
- विशेषताएँ :
{
"category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"size": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"eid": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"original_triple_sets": {
"feature": {
"otriple_set": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"modified_triple_sets": {
"feature": {
"mtriple_set": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"shape": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"shape_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lex": {
"feature": {
"comment": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lid": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"test_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"dbpedia_links": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"links": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
रिलीज़_v3.0_en
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:web_nlg/release_v3.0_en')
- विवरण :
The WebNLG challenge consists in mapping data to text. The training data consists
of Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation
of these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).
a. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)
b. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot
As the example illustrates, the task involves specific NLG subtasks such as sentence segmentation
(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),
aggregation (how to avoid repetitions) and surface realisation
(how to build a syntactically correct and natural sounding text).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 0.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'dev' | 1667 |
'test' | 5713 |
'train' | 13211 |
- विशेषताएँ :
{
"category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"size": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"eid": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"original_triple_sets": {
"feature": {
"otriple_set": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"modified_triple_sets": {
"feature": {
"mtriple_set": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"shape": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"shape_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lex": {
"feature": {
"comment": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lid": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"test_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"dbpedia_links": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"links": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
रिलीज़_v3.0_ru
इस डेटासेट को TFDS में लोड करने के लिए निम्नलिखित कमांड का उपयोग करें:
ds = tfds.load('huggingface:web_nlg/release_v3.0_ru')
- विवरण :
The WebNLG challenge consists in mapping data to text. The training data consists
of Data/Text pairs where the data is a set of triples extracted from DBpedia and the text is a verbalisation
of these triples. For instance, given the 3 DBpedia triples shown in (a), the aim is to generate a text such as (b).
a. (John_E_Blaha birthDate 1942_08_26) (John_E_Blaha birthPlace San_Antonio) (John_E_Blaha occupation Fighter_pilot)
b. John E Blaha, born in San Antonio on 1942-08-26, worked as a fighter pilot
As the example illustrates, the task involves specific NLG subtasks such as sentence segmentation
(how to chunk the input data into sentences), lexicalisation (of the DBpedia properties),
aggregation (how to avoid repetitions) and surface realisation
(how to build a syntactically correct and natural sounding text).
- लाइसेंस : कोई ज्ञात लाइसेंस नहीं
- संस्करण : 0.0.0
- विभाजन :
| विभाजित करना | उदाहरण |
|---|---|
'dev' | 790 |
'test' | 3410 |
'train' | 5573 |
- विशेषताएँ :
{
"category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"size": {
"dtype": "int32",
"id": null,
"_type": "Value"
},
"eid": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"original_triple_sets": {
"feature": {
"otriple_set": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"modified_triple_sets": {
"feature": {
"mtriple_set": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"shape": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"shape_type": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lex": {
"feature": {
"comment": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lid": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"text": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
}
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"test_category": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"dbpedia_links": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"links": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}