Enriching very large ontologies using the WWW
, 2000 This paper explores the possibility to exploit text on the world wide web in order to enrich the concepts in existing ontologies. First, a method to retrieve documents from the WWW related to a concept is described. These document collections are used 1)
Agirre, Eneko +3 more
core +4 more sources
A State of the Art of Word Sense Induction: A Way Towards Word Sense Disambiguation for Under-Resourced Languages [PDF]
, 2013 Mohammad Nasiruddin
openalex +1 more source
Forming an Integrated Lexical Resource for Word Sense Disambiguation
Forming an Integrated Lexical Resource for Word Sense Disambiguationtext
openaire
Word Sense Disambiguation with Wikipedia Entities: A Survey of Entity Linking Approaches. [PDF]
Entropy (Basel)Simos MA, Makris C.
europepmc +1 more source
A short text entity disambiguation method based on BERT model and shortest path algorithm. [PDF]
Sci RepLiu X +8 more
europepmc +1 more source
STInt: An integrated dataset covering science, technology and industry information in the pharmaceutical field. [PDF]
Sci DataXu S, Liu Z, An X.
europepmc +1 more source
VLibrasBD: A Brazilian Portuguese-Brazilian sign language (Libras) bilingual text dataset designed to support neural machine translation. [PDF]
Data BriefLima MA +7 more
europepmc +1 more source
Enhancing Named Entity Recognition for immunology and immune-mediated disorders. [PDF]
Front ImmunolChen S, Che J, Sun M, Wang Y.
europepmc +1 more source
NERD: Evaluating Named Entity Recognition Tools in the Web of Data [PDF]
, 2011 Rizzo G., Troncy R.
core
PubMed knowledge graph 2.0: Connecting papers, patents, and clinical trials in biomedical science. [PDF]
Sci DataXu J +8 more
europepmc +1 more source