Abstract
We develop Process Execution Graphs (PEG), a document-level representation of real-world wet lab biochemistry protocols, addressing challenges such as cross-sentence relations, long-range coreference, grounding, and implicit arguments. We manually annotate PEGs in a corpus of complex lab protocols with a novel interactive textual simulator that keeps track of entity traits and semantic constraints during annotation. We use this data to develop graph-prediction models, finding them to be good at entity identification and local relation extraction, while our corpus facilitates further exploration of challenging long-range relations.- Anthology ID:
- 2021.eacl-main.187
- Volume:
- Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
- Month:
- April
- Year:
- 2021
- Address:
- Online
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2190–2202
- Language:
- URL:
- https://aclanthology.org/2021.eacl-main.187
- DOI:
- 10.18653/v1/2021.eacl-main.187
- Cite (ACL):
- Ronen Tamari, Fan Bai, Alan Ritter, and Gabriel Stanovsky. 2021. Process-Level Representation of Scientific Protocols with Interactive Annotation. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, pages 2190–2202, Online. Association for Computational Linguistics.
- Cite (Informal):
- Process-Level Representation of Scientific Protocols with Interactive Annotation (Tamari et al., EACL 2021)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2021.eacl-main.187.pdf
- Code
- bflashcp3f/textlabs-xwlp-code + additional community code