Using entity information from a knowledge base to improve relation extraction

Lan Du, Anish Kumar, Mark Johnson, Massimiliano Ciaramita

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review


    Relation extraction is the task of extracting predicate-argument relationships
    between entities from natural language text. This paper investigates whether background information about entities available in knowledge bases such as FreeBase can be used to improve the accuracy of a state-of-the-art relation extraction system. We describe a simple and effective way of incorporating FreeBase’s notable types into a state-of-the-art relation extraction system (Riedel et al., 2013). Experimental results show that our notable typebased
    system achieves an average 7.5% weighted MAP score improvement. To
    understand where the notable type information contributes the most, we perform a series of ablation experiments. Results show that the notable type information improves relation extraction more than NER labels alone across a wide range of entity types and relations.
    Original languageEnglish
    Title of host publicationAustralasian Language Technology Association Workshop 2015
    Subtitle of host publicationProceedings of the Workshop
    EditorsBen Hachey, Kellie Webster
    Place of PublicationMelbourne Vic Australia
    PublisherAustralasian Language Technology Association
    Number of pages8
    Publication statusPublished - 2015
    EventAustralasian Language Technology Association Workshop 2015 - University of Western Sydney, Parramatta, Australia
    Duration: 8 Dec 20159 Dec 2015
    Conference number: 13th (Proceedings)

    Publication series

    NameProceedings of the Australasian Language Technology Workshop
    PublisherAustralasian Language Technology Association
    ISSN (Print)1834-7037


    ConferenceAustralasian Language Technology Association Workshop 2015
    Abbreviated titleALTAW 2015
    OtherALTA 2015 will be co-located with the 2nd Conference of the Australian Music and Psychology Society (AMPS 2015), the 20th Australasian Document Computing Symposium 2014 (ADCS 2015) and the 46th Australian Linguistic Society conference (ALS 2015).
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