trivia_qa

• Description:

TriviaqQA is a reading comprehension dataset containing over 650K question-answer-evidence triples. TriviaqQA includes 95K question-answer pairs authored by trivia enthusiasts and independently gathered evidence documents, six per question on average, that provide high quality distant supervision for answering the questions.

• Additional Documentation: Explore on Papers With Code

• Homepage: http://nlp.cs.washington.edu/triviaqa/

• Source code: tfds.datasets.trivia_qa.Builder

• Versions:

  • 1.1.0 (default): No release notes.

• Feature structure:

FeaturesDict({
    'answer': FeaturesDict({
        'aliases': Sequence(Text(shape=(), dtype=string)),
        'matched_wiki_entity_name': Text(shape=(), dtype=string),
        'normalized_aliases': Sequence(Text(shape=(), dtype=string)),
        'normalized_matched_wiki_entity_name': Text(shape=(), dtype=string),
        'normalized_value': Text(shape=(), dtype=string),
        'type': Text(shape=(), dtype=string),
        'value': Text(shape=(), dtype=string),
    }),
    'entity_pages': Sequence({
        'doc_source': Text(shape=(), dtype=string),
        'filename': Text(shape=(), dtype=string),
        'title': Text(shape=(), dtype=string),
        'wiki_context': Text(shape=(), dtype=string),
    }),
    'question': Text(shape=(), dtype=string),
    'question_id': Text(shape=(), dtype=string),
    'question_source': Text(shape=(), dtype=string),
    'search_results': Sequence({
        'description': Text(shape=(), dtype=string),
        'filename': Text(shape=(), dtype=string),
        'rank': int32,
        'search_context': Text(shape=(), dtype=string),
        'title': Text(shape=(), dtype=string),
        'url': Text(shape=(), dtype=string),
    }),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
answer	FeaturesDict
answer/aliases	Sequence(Text)	(None,)	string
answer/matched_wiki_entity_name	Text		string
answer/normalized_aliases	Sequence(Text)	(None,)	string
answer/normalized_matched_wiki_entity_name	Text		string
answer/normalized_value	Text		string
answer/type	Text		string
answer/value	Text		string
entity_pages	Sequence
entity_pages/doc_source	Text		string
entity_pages/filename	Text		string
entity_pages/title	Text		string
entity_pages/wiki_context	Text		string
question	Text		string
question_id	Text		string
question_source	Text		string
search_results	Sequence
search_results/description	Text		string
search_results/filename	Text		string
search_results/rank	Tensor		int32
search_results/search_context	Text		string
search_results/title	Text		string
search_results/url	Text		string

• Supervised keys (See as_supervised doc): None

• Figure (tfds.show_examples): Not supported.

• Citation:

@article{2017arXivtriviaqa,
       author = { {Joshi}, Mandar and {Choi}, Eunsol and {Weld},
                 Daniel and {Zettlemoyer}, Luke},
        title = "{triviaqa: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension}",
      journal = {arXiv e-prints},
         year = 2017,
          eid = {arXiv:1705.03551},
        pages = {arXiv:1705.03551},
archivePrefix = {arXiv},
       eprint = {1705.03551},
}

trivia_qa/rc (default config)

• Config description: Question-answer pairs where all documents for a given question contain the answer string(s). Includes context from Wikipedia and search results.

• Download size: 2.48 GiB

• Dataset size: 14.99 GiB

• Auto-cached (documentation): No

• Splits:

Split	Examples
'test'	17,210
'train'	138,384
'validation'	18,669

• Examples (tfds.as_dataframe):

trivia_qa/rc.nocontext

• Config description: Question-answer pairs where all documents for a given question contain the answer string(s).

• Download size: 2.48 GiB

• Dataset size: 196.84 MiB

• Auto-cached (documentation): Yes (test, validation), Only when shuffle_files=False (train)

• Splits:

Split	Examples
'test'	17,210
'train'	138,384
'validation'	18,669

• Examples (tfds.as_dataframe):

trivia_qa/unfiltered

• Config description: 110k question-answer pairs for open domain QA where not all documents for a given question contain the answer string(s). This makes the unfiltered dataset more appropriate for IR-style QA. Includes context from Wikipedia and search results.

• Download size: 3.07 GiB

• Dataset size: 27.27 GiB

• Auto-cached (documentation): No

• Splits:

Split	Examples
'test'	10,832
'train'	87,622
'validation'	11,313

• Examples (tfds.as_dataframe):

trivia_qa/unfiltered.nocontext

• Config description: 110k question-answer pairs for open domain QA where not all documents for a given question contain the answer string(s). This makes the unfiltered dataset more appropriate for IR-style QA.

• Download size: 603.25 MiB

• Dataset size: 119.78 MiB

• Auto-cached (documentation): Yes

• Splits:

Split	Examples
'test'	10,832
'train'	87,622
'validation'	11,313

• Examples (tfds.as_dataframe):