CHEW: A Dataset of CHanging Events in Wikipedia
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866929401986285568 |
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| author | Borkakoty, Hsuvas Espinosa-Anke, Luis |
| author_facet | Borkakoty, Hsuvas Espinosa-Anke, Luis |
| contents | We introduce CHEW, a novel dataset of changing events in Wikipedia expressed in naturally occurring text. We use CHEW for probing LLMs for their timeline understanding of Wikipedia entities and events in generative and classification experiments. Our results suggest that LLMs, despite having temporal information available, struggle to construct accurate timelines. We further show the usefulness of CHEW-derived embeddings for identifying meaning shift. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_19116 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | CHEW: A Dataset of CHanging Events in Wikipedia Borkakoty, Hsuvas Espinosa-Anke, Luis Computation and Language Artificial Intelligence Machine Learning We introduce CHEW, a novel dataset of changing events in Wikipedia expressed in naturally occurring text. We use CHEW for probing LLMs for their timeline understanding of Wikipedia entities and events in generative and classification experiments. Our results suggest that LLMs, despite having temporal information available, struggle to construct accurate timelines. We further show the usefulness of CHEW-derived embeddings for identifying meaning shift. |
| title | CHEW: A Dataset of CHanging Events in Wikipedia |
| topic | Computation and Language Artificial Intelligence Machine Learning |
| url | https://arxiv.org/abs/2406.19116 |