Papers by Matias Rojas

1 papers
Simple Yet Powerful: An Overlooked Architecture for Nested Named Entity Recognition (2022.coling-1)

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Challenge: Named Entity Recognition (NER) is an important task in Natural Language Processing that aims to identify text spans belonging to predefined categories.
Approach: They propose to revisit the Multiple LSTM-CRF (MLC) model, a simple, overlooked, yet powerful approach based on training independent sequence labeling models for each entity type.
Outcome: The proposed model achieves state-of-the-art results in the Chilean Waiting List corpus by including pre-trained language models.

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