Dual Long Short-Term Memory Networks for Sub-Character Representation Learning
TABLE II: Comparison with previous state-of-the-art models of results on all four Bakeoff-2005 datasets.
['Models', 'PKU', 'MSR', 'CityU', 'AS']
Our baseline model is Bi-LSTM-CRF trained on each datasets only with pre-trained character embedding (the conventional word2vec), no sub-character enhancement, no radical embeddings. Then we improved it with sub-character information, adding radical embeddings, tying two level embeddings up.