参考文献:
webnlg_challenge_2017
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:web_nlg/webnlg_challenge_2017')
- 説明：
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).
- ライセンス: 既知のライセンスはありません
- バージョン: 0.0.0
- 分割:
| スプリット | 例 |
|---|---|
'dev' | 872 |
'test' | 4615 |
'train' | 6940 |
- 特徴：
{
"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"
}
}
リリース_v1
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:web_nlg/release_v1')
- 説明：
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).
- ライセンス: 既知のライセンスはありません
- バージョン: 0.0.0
- 分割:
| スプリット | 例 |
|---|---|
'full' | 14237 |
- 特徴：
{
"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"
}
}
リリース_v2
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:web_nlg/release_v2')
- 説明：
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).
- ライセンス: 既知のライセンスはありません
- バージョン: 0.0.0
- 分割:
| スプリット | 例 |
|---|---|
'dev' | 1619 |
'test' | 1600 |
'train' | 12876 |
- 特徴：
{
"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
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:web_nlg/release_v2_constrained')
- 説明：
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).
- ライセンス: 既知のライセンスはありません
- バージョン: 0.0.0
- 分割:
| スプリット | 例 |
|---|---|
'dev' | 1594年 |
'test' | 1606 |
'train' | 12895 |
- 特徴：
{
"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"
}
}
リリース_v2.1
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:web_nlg/release_v2.1')
- 説明：
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).
- ライセンス: 既知のライセンスはありません
- バージョン: 0.0.0
- 分割:
| スプリット | 例 |
|---|---|
'dev' | 1619 |
'test' | 1600 |
'train' | 12876 |
- 特徴：
{
"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"
}
}
リリース_v2.1_制約付き
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:web_nlg/release_v2.1_constrained')
- 説明：
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).
- ライセンス: 既知のライセンスはありません
- バージョン: 0.0.0
- 分割:
| スプリット | 例 |
|---|---|
'dev' | 1594年 |
'test' | 1606 |
'train' | 12895 |
- 特徴：
{
"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_ja
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:web_nlg/release_v3.0_en')
- 説明：
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).
- ライセンス: 既知のライセンスはありません
- バージョン: 0.0.0
- 分割:
| スプリット | 例 |
|---|---|
'dev' | 1667年 |
'test' | 5713 |
'train' | 13211 |
- 特徴：
{
"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
次のコマンドを使用して、このデータセットを TFDS にロードします。
ds = tfds.load('huggingface:web_nlg/release_v3.0_ru')
- 説明：
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).
- ライセンス: 既知のライセンスはありません
- バージョン: 0.0.0
- 分割:
| スプリット | 例 |
|---|---|
'dev' | 790 |
'test' | 3410 |
'train' | 5573 |
- 特徴：
{
"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"
}
}