Yukari Yamakawa


Cross-document Event Identity via Dense Annotation
Adithya Pratapa | Zhengzhong Liu | Kimihiro Hasegawa | Linwei Li | Yukari Yamakawa | Shikun Zhang | Teruko Mitamura
Proceedings of the 25th Conference on Computational Natural Language Learning

In this paper, we study the identity of textual events from different documents. While the complex nature of event identity is previously studied (Hovy et al., 2013), the case of events across documents is unclear. Prior work on cross-document event coreference has two main drawbacks. First, they restrict the annotations to a limited set of event types. Second, they insufficiently tackle the concept of event identity. Such annotation setup reduces the pool of event mentions and prevents one from considering the possibility of quasi-identity relations. We propose a dense annotation approach for cross-document event coreference, comprising a rich source of event mentions and a dense annotation effort between related document pairs. To this end, we design a new annotation workflow with careful quality control and an easy-to-use annotation interface. In addition to the links, we further collect overlapping event contexts, including time, location, and participants, to shed some light on the relation between identity decisions and context. We present an open-access dataset for cross-document event coreference, CDEC-WN, collected from English Wikinews and open-source our annotation toolkit to encourage further research on cross-document tasks.


pdf bib
Interoperable Annotation of Events and Event Relations across Domains
Jun Araki | Lamana Mulaffer | Arun Pandian | Yukari Yamakawa | Kemal Oflazer | Teruko Mitamura
Proceedings 14th Joint ACL - ISO Workshop on Interoperable Semantic Annotation

Textual Entailment based Question Generation
Takaaki Matsumoto | Kimihiro Hasegawa | Yukari Yamakawa | Teruko Mitamura
Proceedings of the Workshop on Intelligent Interactive Systems and Language Generation (2IS&NLG)


Event Nugget and Event Coreference Annotation
Zhiyi Song | Ann Bies | Stephanie Strassel | Joe Ellis | Teruko Mitamura | Hoa Trang Dang | Yukari Yamakawa | Sue Holm
Proceedings of the Fourth Workshop on Events

Generating Questions and Multiple-Choice Answers using Semantic Analysis of Texts
Jun Araki | Dheeraj Rajagopal | Sreecharan Sankaranarayanan | Susan Holm | Yukari Yamakawa | Teruko Mitamura
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers

We present a novel approach to automated question generation that improves upon prior work both from a technology perspective and from an assessment perspective. Our system is aimed at engaging language learners by generating multiple-choice questions which utilize specific inference steps over multiple sentences, namely coreference resolution and paraphrase detection. The system also generates correct answers and semantically-motivated phrase-level distractors as answer choices. Evaluation by human annotators indicates that our approach requires a larger number of inference steps, which necessitate deeper semantic understanding of texts than a traditional single-sentence approach.


Event Nugget Annotation: Processes and Issues
Teruko Mitamura | Yukari Yamakawa | Susan Holm | Zhiyi Song | Ann Bies | Seth Kulick | Stephanie Strassel
Proceedings of the The 3rd Workshop on EVENTS: Definition, Detection, Coreference, and Representation