EventFull: Complete and Consistent Event Relation Annotation
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866915068914958336 |
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| author | Eirew, Alon Nachshoni, Eviatar Slobodkin, Aviv Dagan, Ido |
| author_facet | Eirew, Alon Nachshoni, Eviatar Slobodkin, Aviv Dagan, Ido |
| contents | Event relation detection is a fundamental NLP task, leveraged in many downstream applications, whose modeling requires datasets annotated with event relations of various types. However, systematic and complete annotation of these relations is costly and challenging, due to the quadratic number of event pairs that need to be considered. Consequently, many current event relation datasets lack systematicity and completeness. In response, we introduce \textit{EventFull}, the first tool that supports consistent, complete and efficient annotation of temporal, causal and coreference relations via a unified and synergetic process. A pilot study demonstrates that EventFull accelerates and simplifies the annotation process while yielding high inter-annotator agreement. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_12733 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | EventFull: Complete and Consistent Event Relation Annotation Eirew, Alon Nachshoni, Eviatar Slobodkin, Aviv Dagan, Ido Computation and Language Event relation detection is a fundamental NLP task, leveraged in many downstream applications, whose modeling requires datasets annotated with event relations of various types. However, systematic and complete annotation of these relations is costly and challenging, due to the quadratic number of event pairs that need to be considered. Consequently, many current event relation datasets lack systematicity and completeness. In response, we introduce \textit{EventFull}, the first tool that supports consistent, complete and efficient annotation of temporal, causal and coreference relations via a unified and synergetic process. A pilot study demonstrates that EventFull accelerates and simplifies the annotation process while yielding high inter-annotator agreement. |
| title | EventFull: Complete and Consistent Event Relation Annotation |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2412.12733 |