A Rule-Based Approach to Extracting Relations from Music Tidbits

TitleA Rule-Based Approach to Extracting Relations from Music Tidbits
Publication TypeConference Paper
Year of Publication2015
Conference Name2nd Workshop on Knowledge Extraction from Text, WWW 2015
AuthorsOramas, S., Sordo M., & Espinosa-Anke L.
Conference Start Date18/05/2015
PublisherSheridan Communications
Conference LocationFlorence, Italy
KeywordsDependency Parsing, information extraction, music information retrieval, Relation Extraction
AbstractThis paper presents a rule based approach to extracting relations from unstructured music text sources. The proposed approach identifies and disambiguates musical entities in text, such as songs, bands, persons, albums and music genres. Candidate relations are then obtained by traversing the dependency parsing tree of each sentence in the text with at least two identified entities. A set of syntactic rules based on part of speech tags are defined to filter out spurious and irrelevant relations. The extracted entities and relations are finally represented as a knowledge graph. We test our method on texts from songfacts.com, a website that provides tidbits with facts and stories about songs. The extracted relations are evaluated intrinsically by assessing their linguistic quality, as well as extrinsically by assessing the extent to which they map an existing music knowledge base. We present encouraging results in both evaluations since our system produces a vast percentage of linguistically correct relations between entities, and is able to replicate a large part of the knowledge base.
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