Monica Monachini

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Optimizing the production, maintenance and extension of lexical resources is one the crucial aspects impacting Natural Language Processing (NLP). A second aspect involves optimizing the process leading to their integration in applications. With this respect, we believe that the production of a consensual specification on lexicons can be a useful aid for the(More)
In this paper we present Wordnet-LMF, a dialect of ISO Lexical Markup Framework that instantiates LMF for representing wordnets. Wordnet-LMF was developed in the framework of the EU KYOTO project for the specific purpose of endowing a set of wordnets with a standardized interoperability format allowing the interchange of lexico-semantic information encoded(More)
The project LE-SIMPLE is an innovative attempt of building harmonized syntactic-semantic lexicons for 12 European languages, aimed at use in different Human Language Technology applications. SIMPLE provides a general design model for the encoding of a large amount of semantic information, spanning from ontological typing, to argument structure and(More)
Domain portability and adaptation of NLP components and Word Sense Disambiguation systems present new challenges. The difficulties found by supervised systems to adapt might change the way we assess the strengths and weaknesses of supervised and knowledgebased WSD systems. Unfortunately, all existing evaluation datasets for specific domains are(More)
CLIPS is a multi-layered Italian computational lexicon based on the PAROLE-SIMPLE model. In this paper we briefly recall the main characteristics of the model and devote our attention to issues emerging from the encoding of large quantities of data, especially in relation to those types of syntactic and semantic information specific to our lexicon and that(More)
We have successfully adapted and extended the automatic Multilingual, Interoperable Named Entity Lexicon approach to Arabic, using Arabic WordNet (AWN) and Arabic Wikipedia (AWK). First, we extract AWN’s instantiable nouns and identify the corresponding categories and hyponym subcategories in AWK. Then, we exploit Wikipedia inter-lingual links to locate(More)
Due to the rapidly expanding body of biomedical literature, biologists require increasingly sophisticated and efficient systems to help them to search for relevant information. Such systems should account for the multiple written variants used to represent biomedical concepts, and allow the user to search for specific pieces of knowledge (or events)(More)
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(More)
This document describes an open text-mining system that was developed for the Asian-European project KYOTO. The KYOTO system uses an open text representation format and a central ontology to enable extraction of knowledge and facts from large volumes of text in many different languages. We implemented a semantic tagging approach that performs off-line(More)