In the context of the project Music Meets Natural Language Processing, Sergio Oramas and Luis Espinosa are launching a challenge at the Open Knowledge Extraction Challenge 2017 organised in the context of the 17th European Semantic Web Conference (ESW17, May 28th-June 1st, Portoroz, Slovenia). Extended deadline until March 17th. Check all details here, some excerpts copied below, and take part to obtain the financial award!
Task 3: Focused Musical NE Recognition and Linking
The task is composed of two sub tasks focused musical NE recognition and linking. A competing system has to fulfil both tasks. The domain of this task is music, thus the used knowledge base will be MusicBrainz as Linked Data (MBL).
Task 3.1: Focused Musical NE Recognition
This sub task consists of the identification and classification of named entities. The task is limited to a subset of the entities types in MBL, which are defined according to the Music Ontology (mo), i.e., entities of the following types: MusicArtist, SignalGroup and MusicalWork.
A competing system is expected to identify entity mentions in a given text by their start and end index, and to further assign them one of these three predefined types.
Task 3.2: Musical NE Linking
In this sub task a system has to link the recognized entities of the previous sub task to the corresponding resource in MBL.
The recent Tutorial on Natural Language Processing for Music Information Retrieval (NLP for MIR) can be of interest for those working on this topic. Check the material and videos in this link.