Papers with partial word-based model
An Encoding Strategy Based Word-Character LSTM for Chinese NER (N19-1)
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| Challenge: | Existing word-based model can not be trained in batches due to its DAG structure. |
| Approach: | They propose a lattice model that integrates word information into the start or end characters of a word and integrates it into a fixed-sized representation for efficient batch training. |
| Outcome: | The proposed model outperforms other state-of-the-art models on benchmark datasets and shows that it can be trained in batches without a shortcut path. |