Datasets:
Tasks:
Text Classification
Sub-tasks:
multi-class-classification
Size:
100K<n<1M
ArXiv:
Tags:
relation extraction
License:
Update README.md
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README.md
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### Dataset Summary
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MultiTACRED is a multilingual version of the large-scale [https://nlp.stanford.edu/projects/tacred/](TAC Relation
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Extraction Dataset). It covers 12 typologically diverse languages from 9 language families, and was created by the
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Speech & Language Technology group of DFKI by machine-translating the instances of the
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automatically projecting their entity annotations. For details of the original TACRED's
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annotation process, see the [https://aclanthology.org/D17-1004/
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validated by checking the correctness of the XML tag markup. Any translations with an invalid tag
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missing or invalid head or tail tag pairs, are discarded (on average, 2.3% of the instances).
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Languages covered are: Arabic, Chinese, Finnish, French, German, Hindi, Hungarian, Japanese, Polish,
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Russian, Spanish, Turkish. Intended use is supervised relation classification. Audience - researchers.
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Please see [https://arxiv.org/abs/2305.04582
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NOTE: This Datasetreader supports a reduced version of the original TACRED JSON format with the following changes:
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NOTE 2: The MultiTACRED dataset offers an additional 'split', namely the backtranslated test data (translated to a
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target language and then back to English). To access this split, use dataset['backtranslated_test'].
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You can find the TACRED dataset reader for the English version of the dataset
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### Supported Tasks and Leaderboards
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- **Tasks:** Relation Classification
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### Dataset Summary
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MultiTACRED is a multilingual version of the large-scale [https://nlp.stanford.edu/projects/tacred/](TAC Relation
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Extraction Dataset). It covers 12 typologically diverse languages from 9 language families, and was created by the
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[Speech & Language Technology group of DFKI](https://www.dfki.de/slt) by machine-translating the instances of the
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original TACRED dataset and automatically projecting their entity annotations. For details of the original TACRED's
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data collection and annotation process, see the [Stanford paper](https://aclanthology.org/D17-1004/). Translations are
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syntactically validated by checking the correctness of the XML tag markup. Any translations with an invalid tag
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structure, e.g. missing or invalid head or tail tag pairs, are discarded (on average, 2.3% of the instances).
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Languages covered are: Arabic, Chinese, Finnish, French, German, Hindi, Hungarian, Japanese, Polish,
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Russian, Spanish, Turkish. Intended use is supervised relation classification. Audience - researchers.
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Please see [our ACL paper](https://arxiv.org/abs/2305.04582) for full details.
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NOTE: This Datasetreader supports a reduced version of the original TACRED JSON format with the following changes:
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- Removed fields: stanford_pos, stanford_ner, stanford_head, stanford_deprel, docid
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NOTE 2: The MultiTACRED dataset offers an additional 'split', namely the backtranslated test data (translated to a
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target language and then back to English). To access this split, use dataset['backtranslated_test'].
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You can find the TACRED dataset reader for the English version of the dataset at
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[https://huggingface.co/datasets/DFKI-SLT/tacred](https://huggingface.co/datasets/DFKI-SLT/tacred).
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### Supported Tasks and Leaderboards
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- **Tasks:** Relation Classification
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