Papers by Jai Riley
Semi-Automated Construction of Sense-Annotated Datasets for Practically Any Language (2025.coling-main)
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Jai Riley, Bradley M. Hauer, Nafisa Sadaf Hriti, Guoqing Luo, Amir Reza Mirzaei, Ali Rafiei, Hadi Sheikhi, Mahvash Siavashpour, Mohammad Tavakoli, Ning Shi, Grzegorz Kondrak
| Challenge: | Word sense disambiguation is a widely studied NLP task of identifying the meaning of a word in context. |
| Approach: | They propose a method to create parallel sense-annotated datasets in English . they use machine translation, word alignment, sense projection, and sense filtering to produce silver annotations . |
| Outcome: | The proposed method produces parallel sense-annotated datasets on Farsi, Chinese, and Bengali . the results are higher than those obtained with recent multilingual systems, the authors say . |
Paraphrase Identification via Textual Inference (2024.starsem-1)
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| Challenge: | Paraphrase identification (PI) and natural language inference (NLI) are important tasks in natural language processing. |
| Approach: | They propose a method for paraphrase identification and natural language inference using an NLI system to solve these tasks. |
| Outcome: | The proposed method outperforms dedicated PI models on PI datasets and provides insights into limitations of current benchmarks. |