An Entity Linking Agent for Question Answering
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , , , , , , , |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866914583782883328 |
|---|---|
| author | Luo, Yajie Wu, Yihong Li, Muzhi Sun, Jia Ao Wang, Xinyu Ma, Liheng Zhang, Yingxue Nie, Jian-Yun |
| author_facet | Luo, Yajie Wu, Yihong Li, Muzhi Sun, Jia Ao Wang, Xinyu Ma, Liheng Zhang, Yingxue Nie, Jian-Yun |
| contents | Some Question Answering (QA) systems rely on knowledge bases (KBs) to provide accurate answers. Entity Linking (EL) plays a critical role in linking natural language mentions to KB entries. However, most existing EL methods are designed for long contexts and do not perform well on short, ambiguous user questions in QA tasks. We propose an entity linking agent for QA, based on a Large Language Model that simulates human cognitive workflows. The agent actively identifies entity mentions, retrieves candidate entities, and makes decision. To verify the effectiveness of our agent, we conduct two experiments: tool-based entity linking and QA task evaluation. The results confirm the robustness and effectiveness of our agent. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_03865 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | An Entity Linking Agent for Question Answering Luo, Yajie Wu, Yihong Li, Muzhi Sun, Jia Ao Wang, Xinyu Ma, Liheng Zhang, Yingxue Nie, Jian-Yun Computation and Language Some Question Answering (QA) systems rely on knowledge bases (KBs) to provide accurate answers. Entity Linking (EL) plays a critical role in linking natural language mentions to KB entries. However, most existing EL methods are designed for long contexts and do not perform well on short, ambiguous user questions in QA tasks. We propose an entity linking agent for QA, based on a Large Language Model that simulates human cognitive workflows. The agent actively identifies entity mentions, retrieves candidate entities, and makes decision. To verify the effectiveness of our agent, we conduct two experiments: tool-based entity linking and QA task evaluation. The results confirm the robustness and effectiveness of our agent. |
| title | An Entity Linking Agent for Question Answering |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2508.03865 |