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MasakhaNER: Named entity recognition for African languages
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In: EISSN: 2307-387X ; Transactions of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03350962 ; Transactions of the Association for Computational Linguistics, The MIT Press, 2021, ⟨10.1162/tacl⟩ (2021)
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Evaluating the Morphosyntactic Well-formedness of Generated Texts ...
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Explorations in Transfer Learning for OCR Post-Correction ...
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Evaluating the Morphosyntactic Well-formedness of Generated Texts ...
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Lexically Aware Semi-Supervised Learning for OCR Post-Correction ...
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Lexically-Aware Semi-Supervised Learning for OCR Post-Correction ...
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Dependency Induction Through the Lens of Visual Perception ...
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Dependency Induction Through the Lens of Visual Perception ...
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AlloVera: a multilingual allophone database
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In: LREC 2020: 12th Language Resources and Evaluation Conference ; https://halshs.archives-ouvertes.fr/halshs-02527046 ; LREC 2020: 12th Language Resources and Evaluation Conference, European Language Resources Association, May 2020, Marseille, France ; https://lrec2020.lrec-conf.org/ (2020)
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A Summary of the First Workshop on Language Technology for Language Documentation and Revitalization ...
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Temporally-Informed Analysis of Named Entity Recognition ...
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Temporally-Informed Analysis of Named Entity Recognition ...
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Abstract:
This repository contains the data set developed for the paper: “Shruti Rijhwani and Daniel Preoțiuc-Pietro. Temporally-Informed Analysis of Named Entity Recognition. In Proceedings of the Association for Computational Linguistics (ACL). 2020.” It includes 12,000 tweets annotated for the named entity recognition task. The tweets are uniformly distributed over the years 2014-2019, with 2,000 tweets from each year. The goal is to have a temporally diverse corpus to account for data drift over time when building NER models. The entity types annotated are locations (LOC), persons (PER) and organizations (ORG). The tweets are preprocessed to replace usernames and URLs with a unique token. Hashtags are left intact and can be annotated as named entities. Format The repository contains the annotations in JSON format. Each year-wise file has the tweet IDs along with token-level annotations. The Public Twitter Search API (https://developer.twitter.com/en/docs/tweets/search) can be used extract the text for the tweet ...
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Keyword:
information extraction; named entity recognition; ner; temporal analysis; tweets; twitter; twitter ner
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URL: https://zenodo.org/record/3899040 https://dx.doi.org/10.5281/zenodo.3899040
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AlloVera: a multilingual allophone database
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In: LREC 2020: 12th Language Resources and Evaluation Conference ; https://halshs.archives-ouvertes.fr/halshs-02527046 ; LREC 2020: 12th Language Resources and Evaluation Conference, European Language Resources Association, May 2020, Marseille, France ; https://lrec2020.lrec-conf.org/ (2020)
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Improving Candidate Generation for Low-resource Cross-lingual Entity Linking
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In: Transactions of the Association for Computational Linguistics, Vol 8, Pp 109-124 (2020) (2020)
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Zero-shot Neural Transfer for Cross-lingual Entity Linking ...
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