Papers with named entity recognizer
Improving Text-to-SQL Semantic Parsing with Fine-grained Query Understanding (2022.emnlp-industry)
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Jun Wang, Patrick Ng, Alexander Hanbo Li, Jiarong Jiang, Zhiguo Wang, Bing Xiang, Ramesh Nallapati, Sudipta Sengupta
| Challenge: | Recent research on Text-to-SQL semantic parsing relies on parser or heuristic based approach to understand natural language query. |
| Approach: | They propose a general-purpose, modular neural semantic parsing framework that is based on token-level fine-grained query understanding. |
| Outcome: | The proposed framework outperforms the state-of-the-art model by 2.7% on a WikiTableQuestions test set. |
Dependency-Guided LSTM-CRF for Named Entity Recognition (D19-1)
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| Challenge: | Named entity recognition (NER) is one of the most important and fundamental tasks in natural language processing (NLP). |
| Approach: | They propose a dependency-guided model to encode dependency trees and capture their properties for named entity recognition. |
| Outcome: | The proposed model improves named entity recognition performance on standard datasets. |