The materials science procedural text corpus: Annotating materials synthesis procedures with shallow semantic structures
Name
1905.06939.pdf
Description
Accepted version
Size
349.5 KB
Format
Unknown
Checksum (MD5)
e3925d49fc06cf218be6f0cf2f6d2131
Author(s)
Mysore, Sheshera
Jensen, Zach
Kim, Edward
Huang, Kevin Joon-Ming
Chang, Haw-Shiuan
Strubell, Emma
Flanigan, Jeffrey
McCallum, Andrew
Olivetti, Elsa A.
Date Issued
July 2019
Journal
LAW 2019 - 13th Linguistic Annotation Workshop, Proceedings of the Workshop
Citation
2019. "The materials science procedural text corpus: Annotating materials synthesis procedures with shallow semantic structures." LAW 2019 - 13th Linguistic Annotation Workshop, Proceedings of the Workshop.
Version
Author's final manuscript
Abstract
© 2019 Association for Computational Linguistics Materials science literature contains millions of materials synthesis procedures described in unstructured natural language text. Large-scale analysis of these synthesis procedures would facilitate deeper scientific understanding of materials synthesis and enable automated synthesis planning. Such analysis requires extracting structured representations of synthesis procedures from the raw text as a first step. To facilitate the training and evaluation of synthesis extraction models, we introduce a dataset of 230 synthesis procedures annotated by domain experts with labeled graphs that express the semantics of the synthesis sentences. The nodes in this graph are synthesis operations and their typed arguments, and labeled edges specify relations between the nodes. We describe this new resource in detail and highlight some specific challenges to annotating scientific text with shallow semantic structure. We make the corpus available to the community to promote further research and development of scientific information extraction systems.
MIT Department
Massachusetts Institute of Technology. Department of Materials Science and Engineering
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://www.aclweb.org/anthology/W19-4007.pdf
