Abstract
In this paper we report the participation of ADEL to the OKE 2017 challenge. In particular, an adaptive entity recognition and linking framework that combines various extraction methods for improving the recognition level and implements an efficient knowledge base indexing process to increase the performance of the linking step. We detail how we deal with fine-grained entity types, either generic (e.g. Activity, Competition, Animal for Task 2) or domain specific (e.g. MusicArtist, SignalGroup, MusicalWork for Task 3). We also show how ADEL can flexibly link entities from different knowledge bases (DBpedia and MusicBrainz). We obtain promising results on the OKE 2017 challenge test dataset for the first three tasks.
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References
Huang, P.-S., He, X., Gao, J., Deng, L., Acero, A., Heck, L.: Learning deep structured semantic models for web search using clickthrough data. In: 22nd ACM International Conference on Information & Knowledge Management (CIKM) (2013)
Manning, C.D., Surdeanu, M., Bauer, J., Finkel, J., Bethard, S.J., McClosky, D.: The stanford coreNLP natural language processing toolkit. In: Association for Computational Linguistics (ACL) System Demonstrations (2014)
Plu, J., Rizzo, G., Troncy, R.: A hybrid approach for entity recognition and linking. In: 12th European Semantic Web Conference (ESWC), Open Knowledge Extraction Challenge (2015)
Plu, J., Rizzo, G., Troncy, R.: Enhancing entity linking by combining NER models. In: 13th European Semantic Web Conference (ESWC), Open Knowledge Extraction Challenge (2016)
Plu, J., Rizzo, G., Troncy, R.: ADEL: adaptable entity linking. Semant. Web J. (SWJ) Spec. Issue Linked Data Inf. Extr. (2017)
Rizzo, G., van Erp, M., Troncy, R.: Inductive entity typing alignment. In: 2nd International Workshop on Linked Data for Information Extraction (LD4IE) (2014)
Speck, R., Ngomo, A
Usbeck, R., Ngomo, A., Röder, M., Gerber, D., Coelho, S., Auer, S., Both, A.: AGDISTIS - graph-based disambiguation of named entities using linked data. In: The Semantic Web–ISWC 2014 (2014)
Acknowledgments
This work was primarily supported by the innovation activity PasTime (17164) of EIT Digital (https://www.eitdigital.eu).
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Plu, J., Troncy, R., Rizzo, G. (2017). ADEL@OKE 2017: A Generic Method for Indexing Knowledge Bases for Entity Linking. In: Dragoni, M., Solanki, M., Blomqvist, E. (eds) Semantic Web Challenges. SemWebEval 2017. Communications in Computer and Information Science, vol 769. Springer, Cham. https://doi.org/10.1007/978-3-319-69146-6_5
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DOI: https://doi.org/10.1007/978-3-319-69146-6_5
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