Social media content represents a large portion of all textual content appearing on the
Internet. These streams of user generated content (UGC) provide an opportunity and …

Social media content represents a large portion of all textual content appearing on the
Internet. These streams of user generated content (UGC) provide an opportunity and …

Named entity extraction and disambiguation have received much attention in recent years.
Typical fields addressing these topics are information retrieval, natural language processing …

Abstract Named Entity Disambiguation (NED) algorithms disambiguate mentions of named
entities with respect to a knowledge-base, but sometimes the context might be poor or …

Named Entity Disambiguation is the task of disambiguating named entity mentions in
unstructured text and linking them to their corresponding entries in a large knowledge base …

Semantic annotation of named entities for enriching unstructured content is a critical step in
development of Semantic Web and many Natural Language Processing applications. To this …

We address the Named Entity Disambiguation (NED) problem for short, user-generated texts
on the social Web. In such settings, the lack of linguistic features and sparse lexical context …

The rapidly increasing use of large-scale data on the Web has made named entity
disambiguation a key research challenge in Information Extraction (IE) and development of …

The rapidly increasing use of large-scale data on the Web makes named entity
disambiguation become one of the main challenges to research in Information Extraction …

Abstract Knowledge bases (KBs), repositories consisting of entities, facts about entities, and
relations between entities, are a vital component for many tasks in artificial intelligence and …