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Exploring a Probabilistic Earley Parser for Event Composition in Biomedical Texts

Mai Vu Tran and Hoang Quynh Le and Van Thuy Phi and Thanh Binh Pham and Collier Nigel (2016) Exploring a Probabilistic Earley Parser for Event Composition in Biomedical Texts. In: SW4PHD: the 2016 Scientific Workshop for PhD Students, 26 March 2016, Hanoi.

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Abstract

We describe a high precision system for extracting events of biomedical significance that was developed during the BioNLP shared task 2013 and tested on the Cancer Genetics data set. Our system explored a multi-stage approach including trigger detection, edge detection and event composition. After trigger edge detection is finished we are left with a semantic graph from which we must select the optimal subset that is consistent with the semantic frames for each event type. The system achieved an F-score on the development data of 73.67 but was ranked 5th out of six with an F-score of 29.94 on the test data. How-ever, precision was the second highest ranked on the task at 62.73. Analysis suggests the need to continue to improve our system for complex events particularly taking into account cross-domain differences in argument distributions.

Item Type:Conference or Workshop Item (Poster)
Subjects:Information Technology (IT)
Divisions:Faculty of Information Technology (FIT)
ID Code:1550
Deposited By: Dr Ngoc Thang Bui
Deposited On:23 May 2016 03:00
Last Modified:23 May 2016 03:01

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