Proper names represent about 10% of English or French newspaper articles. Their quantity and informational quality is already used in different Information Extraction systems. Proper names have widely been studied in the MUC conferences designed to promote research in Information Extraction. We have created our own named entity extraction tool based on a linguistic description with automata. Th...

Many speech applications, most prominently telephone directory assistance, require the recognition of proper names. However, the recognition of increasingly large sets of spoken names is di cult: Besides technical limitations, very large recognition vocabularies contain many easily confused words or even homophones. Therefore, proper names are often spelled or both spoken and spelled. In this p...

Among the resources developed in SI-TAL (Integrated Systems for the Automatic Treatment of Language), ItalWordNet (IWN) was built as reference semantic database, enlarging the Italian WordNet developed in the framework of the European project EuroWordNet (EWN). The Italian lexical database was increased, by introducing and codifying, besides the new grammatical categories of the adjectives and ...

This paper describes a supervised learning method to automatically select from a set of noun phrases, embedding proper names of different semantic classes, their most distinctive features. The result of the learning process is a decision tree which classifies an unknown proper name on the basis of its context of occurrence. This classifier is used to estimate the probability distribution of an ...

The identification of unknown proper names in text is a significant challenge for NLP systems operating on unrestricted text. A system which indexes documents according to name references can be useful for information retrieval or as a preprocessor for more knowledge intensive tasks such as database extraction. This paper describes a system which uses text skimming techniques for deriving prope...

Implemented methods for proper names recognition rely on large gazetteers of common proper nouns and a set of heuristic rules (e.g. Mr. as an indicator of a PERSON entity type). Though the performance of current PN recognizers is very high (over 90%), it is important to note that this problem is by no means a "solved problem". Existing systems perform extremely well on newswire corpora by virtu...

This paper shows rst the problems raised by proper names in natural language processing. Second, it introduces the knowledge representation structure we use based on conceptual graphs. Then it explains the techniques which are used to process known and unknown proper names. At last, it gives the performance of the system and the further works we intend to deal with.

This paper shows first the problems raised by proper names in natural language processing. Second, it introduces the knowledge representation structure we use based on conceptual graphs. Then it explains the techniques which are used to process known and unknown proper names. At last, it gives the performance of the system and the further works we intend to deal with. or unknown. Some of these ...

Proper Names are a frequent occurrence in all types of natural language text. However, the treatment of proper names is an area under-researched by Natural Language Processing. One particular problem is how to link information about the same entity referred to by possibly different proper names in several documents. In this paper we describe a prototype system which first pre-processes individu...