Referências:
webnlg_challenge_2017
Use o seguinte comando para carregar esse conjunto de dados no TFDS:
ds = tfds.load('huggingface:web_nlg/webnlg_challenge_2017')
- Descrição :
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).
- Licença : Nenhuma licença conhecida
- Versão : 0.0.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'dev' | 872 |
'test' | 4615 |
'train' | 6940 |
- Características :
{
"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"
}
}
versão_v1
Use o seguinte comando para carregar esse conjunto de dados no TFDS:
ds = tfds.load('huggingface:web_nlg/release_v1')
- Descrição :
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).
- Licença : Nenhuma licença conhecida
- Versão : 0.0.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'full' | 14237 |
- Características :
{
"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"
}
}
versão_v2
Use o seguinte comando para carregar esse conjunto de dados no TFDS:
ds = tfds.load('huggingface:web_nlg/release_v2')
- Descrição :
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).
- Licença : Nenhuma licença conhecida
- Versão : 0.0.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'dev' | 1619 |
'test' | 1600 |
'train' | 12876 |
- Características :
{
"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"
}
}
release_v2_constrained
Use o seguinte comando para carregar esse conjunto de dados no TFDS:
ds = tfds.load('huggingface:web_nlg/release_v2_constrained')
- Descrição :
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).
- Licença : Nenhuma licença conhecida
- Versão : 0.0.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'dev' | 1594 |
'test' | 1606 |
'train' | 12895 |
- Características :
{
"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"
}
}
versão_v2.1
Use o seguinte comando para carregar esse conjunto de dados no TFDS:
ds = tfds.load('huggingface:web_nlg/release_v2.1')
- Descrição :
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).
- Licença : Nenhuma licença conhecida
- Versão : 0.0.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'dev' | 1619 |
'test' | 1600 |
'train' | 12876 |
- Características :
{
"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"
}
}
release_v2.1_constrained
Use o seguinte comando para carregar esse conjunto de dados no TFDS:
ds = tfds.load('huggingface:web_nlg/release_v2.1_constrained')
- Descrição :
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).
- Licença : Nenhuma licença conhecida
- Versão : 0.0.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'dev' | 1594 |
'test' | 1606 |
'train' | 12895 |
- Características :
{
"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"
}
}
release_v3.0_en
Use o seguinte comando para carregar esse conjunto de dados no TFDS:
ds = tfds.load('huggingface:web_nlg/release_v3.0_en')
- Descrição :
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).
- Licença : Nenhuma licença conhecida
- Versão : 0.0.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'dev' | 1667 |
'test' | 5713 |
'train' | 13211 |
- Características :
{
"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"
}
}
release_v3.0_ru
Use o seguinte comando para carregar esse conjunto de dados no TFDS:
ds = tfds.load('huggingface:web_nlg/release_v3.0_ru')
- Descrição :
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).
- Licença : Nenhuma licença conhecida
- Versão : 0.0.0
- Divisões :
| Dividir | Exemplos |
|---|---|
'dev' | 790 |
'test' | 3410 |
'train' | 5573 |
- Características :
{
"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"
}
}