Abstract
This paper presents a novel Cross-document Abstract Meaning Representation (X-AMR) annotation tool designed for annotating key corpus-level event semantics. Leveraging machine assistance through the Prodigy Annotation Tool, we enhance the user experience, ensuring ease and efficiency in the annotation process. Through empirical analyses, we demonstrate the effectiveness of our tool in augmenting an existing event corpus, highlighting its advantages when integrated with GPT-4. Code and annotations: href{https://anonymous.4open.science/r/xamr-9ED0}{anonymous.4open.science/r/xamr-9ED0} footnote Demo: {href{https://youtu.be/TuirftxciNE}{https://youtu.be/TuirftxciNE}} footnote Live Link: {href{https://tinyurl.com/mrxmafwh}{https://tinyurl.com/mrxmafwh}}- Anthology ID:
- 2024.eacl-demo.19
- Original:
- 2024.eacl-demo.19v1
- Version 2:
- 2024.eacl-demo.19v2
- Volume:
- Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
- Month:
- March
- Year:
- 2024
- Address:
- St. Julians, Malta
- Editors:
- Nikolaos Aletras, Orphee De Clercq
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 177–186
- Language:
- URL:
- https://preview.aclanthology.org/add_missing_videos/2024.eacl-demo.19/
- DOI:
- Cite (ACL):
- Shafiuddin Rehan Ahmed, Jon Cai, Martha Palmer, and James H. Martin. 2024. X-AMR Annotation Tool. In Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, pages 177–186, St. Julians, Malta. Association for Computational Linguistics.
- Cite (Informal):
- X-AMR Annotation Tool (Ahmed et al., EACL 2024)
- PDF:
- https://preview.aclanthology.org/add_missing_videos/2024.eacl-demo.19.pdf