All datasets / KelvinJiang

KelvinJiang/freebase_qa

903 downloads in 30 days11 likesLast modified 18 Jan 2024View on Hugging Face

Unclear

The checks could not identify a recognised licence ID in the dataset's metadata.

Declared licence: unknown, from the tagEvidence: README.md at 5c61c7f
Licence files: No licence file at the top level of the repositoryEvidence: file list at 5c61c7f
Declared sources: 1
Access gated on Hugging Face: No

Each cell links to what was checked: a file, a file list or a Hub record.

Sources listed in the card metadata

trivia_qaunknownUnclearEvidence: README.md at 0f7faf3

Tasks

question-answering

Citation text from the card

@inproceedings{jiang-etal-2019-freebaseqa,
    title = "{F}reebase{QA}: A New Factoid {QA} Data Set Matching Trivia-Style Question-Answer Pairs with {F}reebase",
    author = "Jiang, Kelvin  and
      Wu, Dekun  and
      Jiang, Hui",
    booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/N19-1028",
    doi = "10.18653/v1/N19-1028",
    pages = "318--323",
    abstract = "In this paper, we present a new data set, named FreebaseQA, for open-domain factoid question answering (QA) tasks over structured knowledge bases, like Freebase. The data set is generated by matching trivia-type question-answer pairs with subject-predicate-object triples in Freebase. For each collected question-answer pair, we first tag all entities in each question and search for relevant predicates that bridge a tagged entity with the answer in Freebase. Finally, human annotation is used to remove any false positive in these matched triples. Using this method, we are able to efficiently generate over 54K matches from about 28K unique questions with minimal cost. Our analysis shows that this data set is suitable for model training in factoid QA tasks beyond simpler questions since Freebase

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dataset_licence({ "id": "KelvinJiang/freebase_qa" })
signal: "unclear"
stated_licence: "unknown"
sources: 1