Pooled Contextualized Embeddings for Named Entity Recognition

NAACL 2019 Alan AkbikTanja BergmannRol Vollgraf

Contextual string embeddings are a recent type of contextualized word embedding that were shown to yield state-of-the-art results when utilized in a range of sequence labeling tasks. They are based on character-level language models which treat text as distributions over characters and are capable of generating embeddings for any string of characters within any textual context... (read more)

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Evaluation results from the paper

#4 best model for Named Entity Recognition on CoNLL 2003 (English) (using extra training data)

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Task Dataset Model Metric name Metric value Global rank Uses extra
training data
Named Entity Recognition CoNLL 2003 (English) Flair embeddings + Pooling F1 93.18 # 4