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ELMD: An Automatically Generated Entity Linking Gold Standard Dataset in the Music Domain

Title ELMD: An Automatically Generated Entity Linking Gold Standard Dataset in the Music Domain
Publication Type Conference Paper
Year of Publication 2016
Conference Name Language Resources and Evaluation Conference (LREC 2016)
Authors Oramas, S. , Espinosa-Anke L. , Sordo M. , Saggion H. , & Serra X.
Pagination 3312-3317
Conference Start Date 23/05/2016
Conference Location Portorož (Eslovenia)
Abstract In this paper we present a gold standard dataset for Entity Linking (EL) in the Music Domain. It contains thousands of musical named entities such as Artist, Song or Record Label, which have been automatically annotated on a set of artist biographies coming from the Music website and social network Last.fm. The annotation process relies on the analysis of the hyperlinks present in the source texts and in a voting-based algorithm for EL, which considers, for each entity mention in text, the degree of agreement across three state-of-the-art EL systems. Manual evaluation shows that EL Precision is at least 94%, and due to its tunable nature, it is possible to derive annotations favouring higher Precision or Recall, at will. We make available the annotated dataset along with evaluation data and the code.
preprint/postprint document https://repositori.upf.edu/handle/10230/27835
Additional material:
ELMD Dataset of ∼13k documents and almost 150k annotated musical entities, which are linked to DBpedia and MusicBrainz. From this corpus, a gold standard dataset of 200 documents with manually annotated entities is also created (Section 3.4). http://mtg.upf.edu/download/datasets/elmd