@inproceedings{420202fbc5994fcf89ce0ee5fd720829,
title = "Entity Enabled Relation Linking",
abstract = "Relation linking is an important problem for knowledge graph-based Question Answering. Given a natural language question and a knowledge graph, the task is to identify relevant relations from the given knowledge graph. Since existing techniques for entity extraction and linking are more stable compared to relation linking, our idea is to exploit entities extracted from the question to support relation linking. In this paper, we propose a novel approach, based on DBpedia entities, for computing relation candidates. We have empirically evaluated our approach on different standard benchmarks. Our evaluation shows that our approach significantly outperforms existing baseline systems in both recall, precision and runtime.",
keywords = "Knowledge Graph, Predicate linking, Question answering, Semantic search, Semantic Web",
author = "Pan, {Jeff Z.} and Mei Zhang and Kuldeep Singh and {van Harmelen}, Frank and Jinguang Gu and Zhi Zhang",
year = "2019",
doi = "10.1007/978-3-030-30793-6_30",
language = "English",
isbn = "9783030307929",
volume = "1",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "523--538",
editor = "Chiara Ghidini and Olaf Hartig and Maria Maleshkova and Vojtech Sv{\'a}tek and Isabel Cruz and Aidan Hogan and Jie Song and Maxime Lefran{\c c}ois and Fabien Gandon",
booktitle = "The Semantic Web – ISWC 2019",
note = "18th International Semantic Web Conference, ISWC 2019 ; Conference date: 26-10-2019 Through 30-10-2019",
}