The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures

Sheshera Mysore, Zachary Jensen, Edward Kim, Kevin Huang, Haw-Shiuan Chang, Emma Strubell, Jeffrey Flanigan, Andrew McCallum, Elsa Olivetti


Abstract
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.
Anthology ID:
W19-4007
Volume:
Proceedings of the 13th Linguistic Annotation Workshop
Month:
August
Year:
2019
Address:
Florence, Italy
Venues:
ACL | LAW | WS
SIG:
SIGANN
Publisher:
Association for Computational Linguistics
Note:
Pages:
56–64
Language:
URL:
https://www.aclweb.org/anthology/W19-4007
DOI:
10.18653/v1/W19-4007
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PDF:
http://aclanthology.lst.uni-saarland.de/W19-4007.pdf