Know-Center at SemEval-2017 Task 10: Sequence Classification with the CODE Annotator

Roman Kern, Stefan Falk, Andi Rexha


Abstract
This paper describes our participation in SemEval-2017 Task 10. We competed in Subtask 1 and 2 which consist respectively in identifying all the key phrases in scientific publications and label them with one of the three categories: Task, Process, and Material. These scientific publications are selected from Computer Science, Material Sciences, and Physics domains. We followed a supervised approach for both subtasks by using a sequential classifier (CRF - Conditional Random Fields). For generating our solution we used a web-based application implemented in the EU-funded research project, named CODE. Our system achieved an F1 score of 0.39 for the Subtask 1 and 0.28 for the Subtask 2.
Anthology ID:
S17-2167
Volume:
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
Month:
August
Year:
2017
Address:
Vancouver, Canada
Venue:
SemEval
SIGs:
SIGSEM | SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
961–964
Language:
URL:
https://aclanthology.org/S17-2167
DOI:
10.18653/v1/S17-2167
Bibkey:
Cite (ACL):
Roman Kern, Stefan Falk, and Andi Rexha. 2017. Know-Center at SemEval-2017 Task 10: Sequence Classification with the CODE Annotator. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pages 961–964, Vancouver, Canada. Association for Computational Linguistics.
Cite (Informal):
Know-Center at SemEval-2017 Task 10: Sequence Classification with the CODE Annotator (Kern et al., SemEval 2017)
Copy Citation:
PDF:
https://aclanthology.org/S17-2167.pdf