Predicting entity mentions in scientific literature

Yalung Zheng, Jon Ezeiza, Mehdi Farzanehpour, Jacopo Urbani*

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review


Predicting which entities are likely to be mentioned in scientific articles is a task with significant academic and commercial value. For instance, it can lead to monetary savings if the articles are behind paywalls, or be used to recommend articles that are not yet available. Despite extensive prior work on entity prediction in Web documents, the peculiarities of scientific literature make it a unique scenario for this task. In this paper, we present an approach that uses a neural network to predict whether the (unseen) body of an article contains entities defined in domain-specific knowledge bases (KBs). The network uses features from the abstracts and the KB, and it is trained using open-access articles and authors’ prior works. Our experiments on biomedical literature show that our method is able to predict subsets of entities with high accuracy. As far as we know, our method is the first of its kind and is currently used in several commercial settings.

Original languageEnglish
Title of host publicationThe Semantic Web
Subtitle of host publication16th International Conference, ESWC 2019, Portorož, Slovenia, June 2–6, 2019, Proceedings
EditorsAlasdair J.G. Gray, Krzysztof Janowicz, Karl Hammar, Pascal Hitzler, Miriam Fernández, Vanessa Lopez, Armin Haller, Amrapali Zaveri
PublisherSpringer Verlag
Number of pages15
ISBN (Electronic)9783030213480
ISBN (Print)9783030213473
Publication statusPublished - 2019
Event16th International Semantic Web Conference, ESWC 2019 - Portorož, Slovenia
Duration: 2 Jun 20196 Jun 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11503 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference16th International Semantic Web Conference, ESWC 2019


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