NTNU-1@ScienceIE at SemEval-2017 Task 10: Identifying and Labelling Keyphrases with Conditional Random Fields
Erwin Marsi, Utpal Kumar Sikdar, Cristina Marco, Biswanath Barik, Rune Sætre
Abstract
We present NTNU’s systems for Task A (prediction of keyphrases) and Task B (labelling as Material, Process or Task) at SemEval 2017 Task 10: Extracting Keyphrases and Relations from Scientific Publications (Augenstein et al., 2017). Our approach relies on supervised machine learning using Conditional Random Fields. Our system yields a micro F-score of 0.34 for Tasks A and B combined on the test data. For Task C (relation extraction), we relied on an independently developed system described in (Barik and Marsi, 2017). For the full Scenario 1 (including relations), our approach reaches a micro F-score of 0.33 (5th place). Here we describe our systems, report results and discuss errors.- Anthology ID:
- S17-2162
- 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:
- 938–941
- Language:
- URL:
- https://aclanthology.org/S17-2162
- DOI:
- 10.18653/v1/S17-2162
- Cite (ACL):
- Erwin Marsi, Utpal Kumar Sikdar, Cristina Marco, Biswanath Barik, and Rune Sætre. 2017. NTNU-1@ScienceIE at SemEval-2017 Task 10: Identifying and Labelling Keyphrases with Conditional Random Fields. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pages 938–941, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- NTNU-1@ScienceIE at SemEval-2017 Task 10: Identifying and Labelling Keyphrases with Conditional Random Fields (Marsi et al., SemEval 2017)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/S17-2162.pdf