Learning Information Extraction Rules for Semi-Structured and Free Text
Machine Learning - Special issue on natural language learning
Snowball: extracting relations from large plain-text collections
DL '00 Proceedings of the fifth ACM conference on Digital libraries
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Preemptive information extraction using unrestricted relation discovery
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
A global joint model for semantic role labeling
Computational Linguistics
Tree kernels for semantic role labeling
Computational Linguistics
The importance of syntactic parsing and inference in semantic role labeling
Computational Linguistics
Using Wikipedia to bootstrap open information extraction
ACM SIGMOD Record
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
The effect of syntactic representation on semantic role labeling
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Shallow semantic parsing for spoken language understanding
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
Coupling semi-supervised learning of categories and relations
SemiSupLearn '09 Proceedings of the NAACL HLT 2009 Workshop on Semi-Supervised Learning for Natural Language Processing
Open information extraction from the web
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Open knowledge extraction through compositional language processing
STEP '08 Proceedings of the 2008 Conference on Semantics in Text Processing
A probabilistic model of redundancy in information extraction
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Open information extraction for the web
Open information extraction for the web
Machine reading at the University of Washington
FAM-LbR '10 Proceedings of the NAACL HLT 2010 First International Workshop on Formalisms and Methodology for Learning by Reading
Relation guided bootstrapping of semantic lexicons
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Identifying relations for open information extraction
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Efficient indexing and querying over syntactically annotated trees
Proceedings of the VLDB Endowment
ClausIE: clause-based open information extraction
Proceedings of the 22nd international conference on World Wide Web
Mining semantics for culturomics: towards a knowledge-based approach
Proceedings of the 2013 international workshop on Mining unstructured big data using natural language processing
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Open Information Extraction is a recent paradigm for machine reading from arbitrary text. In contrast to existing techniques, which have used only shallow syntactic features, we investigate the use of semantic features (semantic roles) for the task of Open IE. We compare TextRunner (Banko et al., 2007), a state of the art open extractor, with our novel extractor SRL-IE, which is based on UIUC's SRL system (Punyakanok et al., 2008). We find that SRL-IE is robust to noisy heterogeneous Web data and outperforms TextRunner on extraction quality. On the other hand, TextRunner performs over 2 orders of magnitude faster and achieves good precision in high locality and high redundancy extractions. These observations enable the construction of hybrid extractors that output higher quality results than TextRunner and similar quality as SRL-IE in much less time.