Papers by Charles Lee
To Schedule or not to Schedule: Extracting Task Specific Temporal Entities and Associated Negation Constraints (2020.emnlp-main)
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| Challenge: | Existing models for date-time entity extraction from text are task agnostic, resulting in insufficient results for task specific date-timing extraction. |
| Approach: | They propose a model for extracting subset of date-time entities from text and their negation constraints. |
| Outcome: | The proposed model achieves an absolute gain of 19% f-score points compared to baseline methods in detecting date-time entities relevant to scheduling meetings and a 4% improvement over baseline methods for detecting negation constraints over date-timing entities. |
ScopeIt: Scoping Task Relevant Sentences in Documents (2020.coling-industry)
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| Challenge: | a problem faced by conversational agents working with large documents is the frequent presence of information that is irrelevant to the agent. |
| Approach: | They propose a neural model for scoping relevant information from a large document . they show that the model performs better with emails than existing baselines . |
| Outcome: | The proposed model improves intent detection and entity extraction tasks without drop in recall. |
Multi-Tiered Cantonese Word Segmentation (2024.lrec-main)
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| Challenge: | Existing work on word segmentation for Chinese does not have conventional word boundaries as English does. |
| Approach: | They propose a linguistically motivated, multi-tiered word segmentation system for Cantonese . they propose linguisticly motivated, linguistic-motivated system that can cater to different needs . |
| Outcome: | The proposed system can be adapted to Cantonese corpus data. |
PyCantonese: Cantonese Linguistics and NLP in Python (2022.lrec-1)
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| Challenge: | a limited number of Cantonese-specific datasets are available for PyCantones. |
| Approach: | They introduce PyCantonese, an open-source Python library for Cantonesi linguistics and natural language processing. |
| Outcome: | The proposed library is open-source and available for free for all purposes, including commercial ones. |