Abstract
We describe an effort to annotate a corpus of natural language instructions consisting of 622 wet lab protocols to facilitate automatic or semi-automatic conversion of protocols into a machine-readable format and benefit biological research. Experimental results demonstrate the utility of our corpus for developing machine learning approaches to shallow semantic parsing of instructional texts. We make our annotated Wet Lab Protocol Corpus available to the research community.- Anthology ID:
- N18-2016
- Volume:
- Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans, Louisiana
- Editors:
- Marilyn Walker, Heng Ji, Amanda Stent
- Venue:
- NAACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 97–106
- Language:
- URL:
- https://aclanthology.org/N18-2016
- DOI:
- 10.18653/v1/N18-2016
- Cite (ACL):
- Chaitanya Kulkarni, Wei Xu, Alan Ritter, and Raghu Machiraju. 2018. An Annotated Corpus for Machine Reading of Instructions in Wet Lab Protocols. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), pages 97–106, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- An Annotated Corpus for Machine Reading of Instructions in Wet Lab Protocols (Kulkarni et al., NAACL 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/N18-2016.pdf
- Data
- GENIA