39 research outputs found
Detecting Entities in the Astrophysics Literature: A Comparison of Word-based and Span-based Entity Recognition Methods
Information Extraction from scientific literature can be challenging due to
the highly specialised nature of such text. We describe our entity recognition
methods developed as part of the DEAL (Detecting Entities in the Astrophysics
Literature) shared task. The aim of the task is to build a system that can
identify Named Entities in a dataset composed by scholarly articles from
astrophysics literature. We planned our participation such that it enables us
to conduct an empirical comparison between word-based tagging and span-based
classification methods. When evaluated on two hidden test sets provided by the
organizer, our best-performing submission achieved scores of 0.8307
(validation phase) and 0.7990 (testing phase).Comment: AACL-IJCNLP Workshop on Information Extraction from Scientific
Publications (WIESP 2022