WordNet is a lexical database for English that has been widely
adopted in artificial intelligence and computational linguistics for a
variety of practical applications.
Since WordNet was designed as a lexical database, it exhibits some
limitations when used for knowledge processing applications. Often
one needs to retrieve words that are topically related, but the links
necessary for that operation are not available in WordNet.
The key idea of the Extended WordNet project was to exploit the rich
information contained in the definitional glosses that is now used
primarily by humans to identify correctly the meaning of words. Our
intent is to automatically (1) syntactically parse the glosses, (2)
transform glosses into logical forms and (3) tag semantically the
nouns, verbs, adjectives and adverbs of the glosses. This increases
the connectivity between synsets and provides computer access to a
broader context for each concept.
The Extended Wordnet is an ongoing project. Future versions of
Extended WordNet will be made available.
The Extended WordNet may be used as a Core Knowledge Base for
applications such as Question Answering,
Information Retrieval, Information Extraction, Summarization, Natural
Language Generation, Inferences, and other knowledge intensive
applications. The glosses contain a part of the world knowledge since
they define the most common concepts of the English language.
The Extended WordNet project is funded by the National Science Foundation
. Professor Dan Moldovan is the Principal Investigator and Professor Sanda Harabagiu is the Co-PI.