Rune Sætre

Also published as: Rune Saetre


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
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)

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.


IDI@NTNU at SemEval-2016 Task 6: Detecting Stance in Tweets Using Shallow Features and GloVe Vectors for Word Representation
Henrik Bøhler | Petter Asla | Erwin Marsi | Rune Sætre
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)


Entity-Focused Sentence Simplification for Relation Extraction
Makoto Miwa | Rune Sætre | Yusuke Miyao | Jun’ichi Tsujii
Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010)


From Protein-Protein Interaction to Molecular Event Extraction
Rune Sætre | Makoto Miwa | Kazuhiro Yoshida | Jun’ichi Tsujii
Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task

A Rich Feature Vector for Protein-Protein Interaction Extraction from Multiple Corpora
Makoto Miwa | Rune Sætre | Yusuke Miyao | Jun’ichi Tsujii
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing


Towards Data and Goal Oriented Analysis: Tool Inter-operability and Combinatorial Comparison
Yoshinobu Kano | Ngan Nguyen | Rune Sætre | Kazuhiro Yoshida | Keiichiro Fukamachi | Yusuke Miyao | Yoshimasa Tsuruoka | Sophia Ananiadou | Jun’ichi Tsujii
Proceedings of the Third International Joint Conference on Natural Language Processing: Volume-II

Connecting Text Mining and Pathways using the PathText Resource
Rune Sætre | Brian Kemper | Kanae Oda | Naoaki Okazaki | Yukiko Matsuoka | Norihiro Kikuchi | Hiroaki Kitano | Yoshimasa Tsuruoka | Sophia Ananiadou | Jun’ichi Tsujii
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

Many systems have been developed in the past few years to assist researchers in the discovery of knowledge published as English text, for example in the PubMed database. At the same time, higher level collective knowledge is often published using a graphical notation representing all the entities in a pathway and their interactions. We believe that these pathway visualizations could serve as an effective user interface for knowledge discovery if they can be linked to the text in publications. Since the graphical elements in a Pathway are of a very different nature than their corresponding descriptions in English text, we developed a prototype system called PathText. The goal of PathText is to serve as a bridge between these two different representations. In this paper, we first describe the overall architecture and the interfaces of the PathText system, and then provide some details about the core Text Mining components.

Task-oriented Evaluation of Syntactic Parsers and Their Representations
Yusuke Miyao | Rune Sætre | Kenji Sagae | Takuya Matsuzaki | Jun’ichi Tsujii
Proceedings of ACL-08: HLT

Evaluating the Effects of Treebank Size in a Practical Application for Parsing
Kenji Sagae | Yusuke Miyao | Rune Saetre | Jun’ichi Tsujii
Software Engineering, Testing, and Quality Assurance for Natural Language Processing

Raising the Compatibility of Heterogeneous Annotations: A Case Study on
Yue Wang | Kazuhiro Yoshida | Jin-Dong Kim | Rune Saetre | Jun’ichi Tsujii
Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing