Named Entity Recognition with Bidirectional LSTM-CNNs

TACL 2016 Jason P. C. ChiuEric Nichols

Named entity recognition is a challenging task that has traditionally required large amounts of knowledge in the form of feature engineering and lexicons to achieve high performance. In this paper, we present a novel neural network architecture that automatically detects word- and character-level features using a hybrid bidirectional LSTM and CNN architecture, eliminating the need for most feature engineering... (read more)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Named Entity Recognition Ontonotes v5 (English) Chiu and Nichols (2016) F1 86.19 # 16

Methods used in the Paper