@inproceedings{0ffc5a4f591540a1abb8346d57d22e14,
title = "The NTNU System at SemEval-2017 Task 10: Extracting Keyphrases and Relations from Scientific Publications Using Multiple Conditional Random Fields",
abstract = "This study describes the design of the NTNU system for the ScienceIE task at the SemEval 2017 workshop. We use self-defined feature templates and multiple conditional random fields with extracted features to identify keyphrases along with categorized labels and their relations from scientific publications. A total of 16 teams participated in evaluation scenario 1 (subtasks A, B, and C), with only 7 teams competing in all subtasks. Our best micro-averaging F1 across the three subtasks is 0.23, ranking in the middle among all 16 submissions.",
author = "Lee, {Lung Hao} and Lee, {Kuei Ching} and Tseng, {Yuen Hsien}",
note = "Publisher Copyright: {\textcopyright} 2017 Association for Computational Linguistics; 11th International Workshop on Semantic Evaluations, SemEval 2017, co-located with the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017 ; Conference date: 03-08-2017 Through 04-08-2017",
year = "2017",
language = "???core.languages.en_GB???",
series = "Proceedings of the Annual Meeting of the Association for Computational Linguistics",
publisher = "Association for Computational Linguistics (ACL)",
pages = "951--955",
booktitle = "ACL 2017 - 11th International Workshop on Semantic Evaluations, SemEval 2017, Proceedings of the Workshop",
}