Conference paper Open Access
L3i at SemEval-2022 Task 11: Straightforward Additional Context for Multilingual Named Entity Recognition
Emanuela Boros; Carlos-Emiliano Gonzalez-Gallardo; Jose G. Moreno; Antoine Doucet
This paper summarizes the participation of the L3i laboratory of the University of La Rochelle in the SemEval-2022 Task 11, Multilingual Complex Named Entity Recognition (MultiCoNER). The task focuses on detecting semantically ambiguous and complex entities in short and low-context monolingual and multilingual settings. We argue that using a language-specific and a multilingual language model could improve the performance of multilingual and mixed NER. Also, we consider that using additional contexts from the training set could improve the performance of a NER on short texts. Thus, we propose a straightforward technique for generating additional contexts with and without the presence of entities.
Our findings suggest that, in our internal experimental setup, this approach is promising. However, we ranked above average for the highresource languages and lower than average for low-resource and multilingual models.
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SemEval_2022___28_February_2022___8_pages___L3i_at_SemEval_2022_Task_11__Straightforward_Additional_Context_for_Multilingual_Named_Entity_Recognition.pdf
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- Publication date:
- March 19, 2022
- DOI:
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- Grants:
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European Commission:
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NewsEye - NewsEye: A Digital Investigator for Historical Newspapers (770299)
- EMBEDDIA - Cross-Lingual Embeddings for Less-Represented Languages in European News Media (825153)
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NewsEye - NewsEye: A Digital Investigator for Historical Newspapers (770299)
- Meeting:
- International Workshop on Semantic Evaluation: Task 11 (SemmEval)
- Communities:
- License (for files):
- Creative Commons Attribution 4.0 International