This paper presents the automatic extension of Princeton WordNet with Named Entities (NEs). This new resource is called Named Entity WordNet. Our method maps the noun is-a hierarchy of WordNet to Wikipedia categories, identifies the NEs present in the latter and extracts different information from them such as written variants, definitions, etc. This information is inserted into a NE repository. A module that converts from this generic repository to the WordNet specific format has been developed. The paper explores different aspects of our methodology such as the treatment of polysemous terms, the identification of hyponyms within the Wikipedia categorization system, the identification of Wikipedia articles which are NEs and the design of a...
AbstractWe automatically create enormous, free and multilingual silver-standard training annotations...
An approach for named entity classification based on Wikipedia article infoboxes is described in thi...
Named Entity Recognition and Classification (NERC) is a well-studied NLP task which is typically app...
This paper presents the automatic extension of Princeton WordNet with Named Entities (NEs). This new...
Lexical resource differ from encyclopaedic resources and represent two distinct types of resource co...
Named Entity Recognition and Classification (NERC) is a well-studied NLP task which is typically app...
Over the last 15 years the role of named entities became more and more impor- tant in natural langu...
This paper proposes to enrich RBMT dictionaries with Named Entities (NEs) automatically acquired fro...
This paper proposes to enrich RBMT dictionaries with Named Entities (NEs) automatically acquired fro...
Lexical resource differ from encyclopaedic resources and represent two distinct types of resource co...
This paper proposes to advance in the current state-of-the-art of automatic Language Resource (LR) b...
This paper proposes to advance in the current state-of-the-art of automatic Language Resource (LR) b...
AbstractWe automatically create enormous, free and multilingual silver-standard training annotations...
This paper proposes to advance in the current state-of-the-art of automatic Language Resource (LR) b...
This paper proposes to advance in the current state-of-the-art of automatic Language Resource (LR) b...
AbstractWe automatically create enormous, free and multilingual silver-standard training annotations...
An approach for named entity classification based on Wikipedia article infoboxes is described in thi...
Named Entity Recognition and Classification (NERC) is a well-studied NLP task which is typically app...
This paper presents the automatic extension of Princeton WordNet with Named Entities (NEs). This new...
Lexical resource differ from encyclopaedic resources and represent two distinct types of resource co...
Named Entity Recognition and Classification (NERC) is a well-studied NLP task which is typically app...
Over the last 15 years the role of named entities became more and more impor- tant in natural langu...
This paper proposes to enrich RBMT dictionaries with Named Entities (NEs) automatically acquired fro...
This paper proposes to enrich RBMT dictionaries with Named Entities (NEs) automatically acquired fro...
Lexical resource differ from encyclopaedic resources and represent two distinct types of resource co...
This paper proposes to advance in the current state-of-the-art of automatic Language Resource (LR) b...
This paper proposes to advance in the current state-of-the-art of automatic Language Resource (LR) b...
AbstractWe automatically create enormous, free and multilingual silver-standard training annotations...
This paper proposes to advance in the current state-of-the-art of automatic Language Resource (LR) b...
This paper proposes to advance in the current state-of-the-art of automatic Language Resource (LR) b...
AbstractWe automatically create enormous, free and multilingual silver-standard training annotations...
An approach for named entity classification based on Wikipedia article infoboxes is described in thi...
Named Entity Recognition and Classification (NERC) is a well-studied NLP task which is typically app...