… data in various natural language processing (NLP) tasks. Knowledge graph-based language
… knowledge for NLP tasks, particularly in the biomedical NLP field. However, such models …

… can utilize natural language understanding (NLU) techniques to comprehend and analyze
the content of healthcare documents. This involves tasks such as semantic role labeling, …

… Natural language processing (NLP) has become an increasingly significant role in advancing
… Thus, in this paper, we ranked the importance by semantics analysis as well as reviewing …

… to semantically annotate the results of the UIMA NLP analysis, using Linked Data formalisms,
in order to facilitate interoperability and allow semantic processing … IT frameworks for public …

… attending to words we a priori know are semantically connected. This integration, although
it … in our WSD framework is a contextualized representation of biomedical terms. Building on …

… Natural Language Processing (NLP) techniques and are constantly evolving to accommodate
increasingly complex natural language … integrated into the MONTRA framework to which it …

… recent advances in applying natural language processing (NLP) to … The ability to accurately
capture both semantic and syntactic … within queries of resource description framework (RDF) …

… Natural language processing (NLP) … resource created gold-standard annotations of the
semantics of sentences in notes describing patients with cancer (76). More shared resources, …

… biomedical data are produced in other languages, such as French. Yet a majority of natural
language processing or semantic … (similarly, the US National Library of Medicine can hardly …

… The UMLS Metathesaurus and Semantic Network were further applied to … semantic groups
and semantic types. We selected 56 semantic types within five clinically related semantic …