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Discourse-guided Approaches for Event Coreference Resolution

Series: Department Seminar

Speaker: Prafulla Kumar Choubey, Texas A&M University

Date/Time: Jan 15 11:30:00

Location: CSA Seminar Hall (Room No. 254, First Floor)

Faculty Advisor:

Event coreference resolution aims to determine and cluster event mentions that refer to the same real-world event. A typical event coreference resolution system relies on scoring similarity between event-arguments features of all event-pairs in a document followed by clustering. However, a text document follows the principle of language economy where most of the events are mentioned only once (singletons). Consequently, only certain key events that connect other peripheral events are repeated to organize the content and produce a coherent story. Additionally, events are barely mentioned together with all of their arguments which results in a sparse and scattered distribution of coreferential event mentions. In the talk, I will discuss some of my recent works that address sparsity in coreferential event distribution by developing a holistic approach based on the cues from the document content organization structures in news articles.
Talk Meeting Link:

Speaker Bio:
Prafulla is currently a Ph.D. candidate in the Department of Computer Science and Engineering at Texas A&M University. He is working under the supervision of Prof. Ruihong Huang. In 2014, he got his bachelor's degree in Electrical Engineering from the Indian Institute of Technology (IIT) Roorkee. Before joining Texas A&M in fall 2016, he worked in the system software team at Samsung Research & Development India- Bangalore. His research interests are broadly in natural language processing and machine learning.

Host Faculty: R. Govindarajan