Results 101 to 110 of about 328,579 (213)
English address terms in Australian, British and North American English on Twitter/X
ABSTRACT This study analyses address terms on Twitter/X across three English‐speaking regions: Australia, the United Kingdom and the United States. Using a random sample, we examine the frequency and regional distribution of address forms, including @‐mentions, vocatives, titles, kinship terms and greetings.
Martin Schweinberger, Amir Sheikhan
wiley +1 more source
Bibliometric analysis of 3736 publications (2004–2025) reveals rapid growth in GLP‐1–based T2DM research. The US leads, with Novo Nordisk and Eli Lilly as top contributors. Thematic shifts from glycemic control toward cardiovascular‐kidney‐metabolic outcomes and real‐world evidence, driven by landmark trials like LEADER and REWIND.
Yanbing Wang +6 more
wiley +1 more source
Accelerating knowledge graph and ontology engineering with large language models
Large Language Models bear the promise of significant acceleration of key Knowledge Graph and Ontology Engineering tasks, including ontology modeling, extension, modification, population, alignment, as well as entity disambiguation.
Cogan Shimizu, Pascal Hitzler
doaj +1 more source
Entity Linking Method Based on Prompt Scoring [PDF]
Entity Linking(EL) aims to link mentions in natural language texts to corresponding target entities in the knowledge base. It mainly faces the problem of limited representation capabilities of mentions and candidate entities, which complicates the ...
GUO Junchen, MA Yutang, XIANG Yan, ZHAO Xuedong, GUO Junjun
doaj +1 more source
Sometimes less is more : Romanian word sense disambiguation revisited [PDF]
Recent approaches to Word Sense Disambiguation (WSD) generally fall into two classes: (1) information-intensive approaches and (2) information-poor approaches.
Kübler, Sandra, Dinu, Georgiana
core
Search-based entity disambiguation with document-centric knowledge bases
Entity disambiguation is the task of mapping ambiguous terms in natural-language text to its entities in a knowledge base. One possibility to describe these entities within a knowledge base is via entity-annotated documents (document-centric knowledge ...
Granitzer, Michael +5 more
core +1 more source
Improving Ontology Service-Driven Entity Disambiguation
pages 29 - 38One of the long-standing challenges in natural language processing is uniquely identifying entities in text, which when performed accurately and with formal ontologies, supports efforts such as semantic search and question-answering.
Seyed, Patrice +2 more
core +1 more source
Assessing named entity recognition by using geoscience domain schemas: the case of mineral systems
Named Entity Recognition (NER) is crucial for accurately extracting and classifying specialized domain terms from textual data. This study introduces the Schema for Mineral Systems (SMS), designed through domain characterization, word disambiguation ...
Sandra Paula Villacorta Chambi +7 more
doaj +1 more source
ArGemma: A Multi‐Task Fine‐Tuning Framework for Adapting Gemma to Arabic
ABSTRACT Open‐source large language models (LLMs) have significantly advanced natural language processing (NLP), particularly for English. However, their performance in Arabic has remained limited due to the scarcity of high‐quality datasets and the high computational cost of full fine‐tuning.
Taha Alselwi +2 more
wiley +1 more source
The therapeutic status of drug administration in phase 2 cancer trials is ambiguous, as these studies test efficacy without strong evidence of clinical benefit. Nonetheless, patients face meaningful risks. This review compared efficacy and safety of monotherapy drugs in phase 2 and phase 3 trials across six cancer types.
Charlotte Ouimet +2 more
wiley +1 more source

