Mohamed Sordo


2021

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Proceedings of the 2nd Workshop on NLP for Music and Spoken Audio (NLP4MusA)
Sergio Oramas | Elena Epure | Luis Espinosa-Anke | Rosie Jones | Massimo Quadrana | Mohamed Sordo | Kento Watanabe
Proceedings of the 2nd Workshop on NLP for Music and Spoken Audio (NLP4MusA)

2020

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Proceedings of the 1st Workshop on NLP for Music and Audio (NLP4MusA)
Sergio Oramas | Luis Espinosa-Anke | Elena Epure | Rosie Jones | Mohamed Sordo | Massimo Quadrana | Kento Watanabe
Proceedings of the 1st Workshop on NLP for Music and Audio (NLP4MusA)

2016

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ELMD: An Automatically Generated Entity Linking Gold Standard Dataset in the Music Domain
Sergio Oramas | Luis Espinosa Anke | Mohamed Sordo | Horacio Saggion | Xavier Serra
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

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.