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Update multitacred.py

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  1. multitacred.py +11 -11
multitacred.py CHANGED
@@ -81,18 +81,19 @@ _CITATION = """\
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  """
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  _DESCRIPTION = """\
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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 original TACRED dataset and
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- automatically projecting their entity annotations. For details of the original TACRED's data collection and
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- annotation process, see the [https://aclanthology.org/D17-1004/](original paper). Translations are syntactically
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- validated by checking the correctness of the XML tag markup. Any translations with an invalid tag structure, e.g.
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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](our ACL paper) 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
@@ -108,9 +109,8 @@ _generate_examples()):
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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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- [here](https://huggingface.co/datasets/DFKI-SLT/tacred).
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-
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  """
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  _HOMEPAGE = "https://github.com/DFKI-NLP/MultiTACRED"
 
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  """
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  _DESCRIPTION = """\
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+ MultiTACRED is a multilingual version of the large-scale TAC Relation Extraction Dataset
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+ (https://nlp.stanford.edu/projects/tacred). It covers 12 typologically diverse languages from 9 language families,
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+ and was created by the Speech & Language Technology group of DFKI (https://www.dfki.de/slt) by machine-translating the
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+ instances of the original TACRED dataset and automatically projecting their entity annotations. For details of the
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+ original TACRED's data collection and annotation process, see the Stanford paper (https://aclanthology.org/D17-1004/).
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+ Translations are syntactically validated by checking the correctness of the XML tag markup. Any translations with an
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+ invalid tag structure, e.g. missing or invalid head or tail tag pairs, are discarded (on average, 2.3% of the
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+ 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.
 
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  """
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  _HOMEPAGE = "https://github.com/DFKI-NLP/MultiTACRED"