Corpus ID: 10318045

Identifying Relations for Open Information Extraction

@inproceedings{Fader2011IdentifyingRF,
  title={Identifying Relations for Open Information Extraction},
  author={Anthony Fader and S. Soderland and Oren Etzioni},
  booktitle={EMNLP},
  year={2011}
}
  • Anthony Fader, S. Soderland, Oren Etzioni
  • Published in EMNLP 2011
  • Computer Science
  • Open Information Extraction (IE) is the task of extracting assertions from massive corpora without requiring a pre-specified vocabulary. [...] Key Method We implemented the constraints in the ReVerb Open IE system, which more than doubles the area under the precision-recall curve relative to previous extractors such as TextRunner and woepos. More than 30% of ReVerb's extractions are at precision 0.8 or higher---compared to virtually none for earlier systems. The paper concludes with a detailed analysis of…Expand Abstract
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    References

    SHOWING 1-10 OF 38 REFERENCES
    Open Information Extraction Using Wikipedia
    • 598
    • Highly Influential
    • PDF
    Semantic Role Labeling for Open Information Extraction
    • 78
    • PDF
    The Tradeoffs Between Open and Traditional Relation Extraction
    • 396
    • PDF
    Open Information Extraction from the Web
    • 2,085
    • PDF
    Adapting Open Information Extraction to Domain-Specific Relations
    • 66
    • PDF
    Preemptive Information Extraction using Unrestricted Relation Discovery
    • 258
    • PDF
    Learning Information Extraction Rules for Semi-Structured and Free Text
    • 1,068
    • PDF
    A hybrid approach for extracting semantic relations from texts
    • 35
    • PDF
    Identifying Functional Relations in Web Text
    • 40
    • PDF
    Learning 5000 Relational Extractors
    • 148
    • PDF