Ghent University-IBCN Participation in TAC-KBP 2014 Slot Filling and Cold Start Tasks
نویسندگان
چکیده
This paper presents the system of the UGENT IBCN team for the TAC KBP 2014 slot filling and cold start (slot filling variant) tasks. This was the team’s first participation in both tasks. The slot filling system uses distant supervision to generate training data combined with a noise reduction step, and two different types of classifiers. We show that the noise reduction step significantly improves precision, and propose an application of word embeddings for slot filling.
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