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:
- SIGLEX | SIGSEM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 961–964
- Language:
- URL:
- https://aclanthology.org/S17-2167
- DOI:
- 10.18653/v1/S17-2167
- 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)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/S17-2167.pdf