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University of Texas at Austin KBP 2013 Slot Filling System: Bayesian Logic Programs for Textual Inference (2013)
Yinon Bentor
, Amelia Harrison,
Shruti Bhosale
, and
Raymond Mooney
This document describes the University of Texas at Austin 2013 system for the Knowledge Base Population (KBP) English Slot Filling (SF) task. The UT Austin system builds upon the output of an existing relation extractor by augmenting relations that are explicitly stated in the text with ones that are inferred from the stated relations using probabilistic rules that encode commonsense world knowledge. Such rules are learned from linked open data and are encoded in the form of Bayesian Logic Programs (BLPs), a statistical relational learning framework based on directed graphical models. In this document, we describe our methods for learning these rules, estimating their associated weights, and performing probabilistic and logical inference to infer unseen relations. In the KBP SF task, our system was able to infer several unextracted relations, but its performance was limited by the base level extractor.
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PDF
Citation:
In
Proceedings of the Sixth Text Analysis Conference (TAC 2013)
2013.
Bibtex:
@inproceedings{bentor:tac2013, title={University of Texas at Austin KBP 2013 Slot Filling System: Bayesian Logic Programs for Textual Inference}, author={Yinon Bentor and Amelia Harrison and Shruti Bhosale and Raymond Mooney}, booktitle={Proceedings of the Sixth Text Analysis Conference (TAC 2013)}, url="http://www.cs.utexas.edu/users/ai-labpub-view.php?PubID=127431", year={2013} }
People
Yinon Bentor
Formerly affiliated Ph.D. Student
yinon [at] cs utexas edu
Shruti Bhosale
Formerly affiliated Masters Student
shruti [at] cs utexas edu
Raymond J. Mooney
Faculty
mooney [at] cs utexas edu
Areas of Interest
Information Extraction
Natural Language Processing
Uncertain and Probabilistic Reasoning
Labs
Machine Learning