Linguaggio Naturale e Ontologie. La Semplificazione Testuale come metodo per l'interazione tra uomo e macchina.

Il problema della rappresentazione della conoscenza e', al giorno d'oggi, una delle principali tematiche discusse nell'ambito delle scienze cognitive, linguistiche e di intelligenza artificiale. Il problema che questo lavoro si propone di affrontare e' studiare se, e come, sia possibile permettere all'utente di interagire in linguaggio naturale con tali sistemi descritti da linguaggi logici ad espressivita' ridotta per motivi computazionali. L'obiettivo e' quello di trovare un frammento di linguaggio che sia condiviso da entrambi, senza che l'uomo sia costretto ad interagire usando un linguaggio controllato. A questo fine si sono indagate, con analisi dei corpora, le percentuali di copertura, del linguaggio naturale, dei due tipi di linguaggi logici, quello di querying e quello di descrizione del sistema di rappresentazione della conoscenza. Nel primo caso, essendo emerso che i costrutti non gestibili dal frammento di logica analizzato non ricorrono ad alte frequenze nell'input naturale, si e' ritenuto opportuno gestire le rare situazioni problematiche con due sistemi di semplificazione testuale (senza affrontare una modifica dell'espressivita' del frammento logico): uno che coinvolge un indebolimento semantico della forma logica dei casi che presentano operatori logici particolari (Carbotta, 2007), e un secondo che invece riguarda la semplificazione sintattica di certi tipi di input problematici. Il trade off fra il linguaggio naturale e il linguaggio di descrizione dell'ontologia si e' rivelato piu' difficile da colmare. Data l'alta percentuale di casi non gestibili dal primo frammento di logica studiato, si e' pensato, prima di tutto, di utilizzare un frammento di logica, ancora computazionalmente poco costoso, ma piu' espressivo sul piano linguistico. Il passo successivo ha coinvolto ancora una volta la semplificazione testuale, per quanto riguarda, in questo caso, la parafrasi di quella porzione di input semanticamente compatibile con la logica, ma sintatticamente non gestibile. Per concludere, si puo' quindi affermare come lavorare contemporaneamente sul versante logico e su quello linguistico sia un approccio interessante per la ricerca di un frammento di linguaggio condiviso tra utente e ontologia. Summary in english: Nowadays, knowledge representation systems are one of the main topic in linguistic and cognitive science studies. The aim of this thesis is to focus on the problem of the human computer interaction through free natural language input. Is it possible to interface with a knowledge representation system through natural language? We address the question on which should be the natural language fragment to be used for such a purpose. To this aim, we analyze two different knid of linguistic corpora, in order to study the trade off : between query language supported by an the ontology (specifically CQs queries), and natural language queries, and the trade off between the fragment of description logic that describes the ontology and natural language utterances. In the former, it turns out a very low frequence of logics operator that can not be handled by the querying language; though rare, it is important to deal with those kind of questons; for this reason we describe textual simplification strategy based on semantic weakening strategy. On the other hand, we propose a syntactic text simplification algorithm in order to paraphrase problematics inputs, like indirect speech acts. In the former analysis, it turns out a more troublesome trade off between free natural language input and description language of the ontology. So, at first, we propose to expand the expressivity of logic fragment. Then we use again a text simplification strategy for dealing with cases that , though semantically accepted, need to be syntactically paraphrased in order to be understood by the ontology. We can conclude the aim of finding a suitable fragment is possible and is an interest merging point of linguistic and logic studies: both contributes are important to reach the task

Singling out Legal Knowledge from World Knowledge. An NLP-based Approach

1. Introduction - 2. Background and Motivation - 3. The Term Extraction Approach - 4. Experiments and Results - 5. Evaluation - 5.1. General Evaluation Criteria - 5.2. Discussion of Results - 6. Conclusio

Lessico settoriale e lessico comune nell\u27estrazione di terminologia specialistica da corpora di dominio

The paper tackles the challenging task of automatic domain term extraction, with a specific view to singling out domain terms from common words in different types of specialized corpora.Il presente contributo descrive un approccio basato su strumenti di Trattamento Automatico del Linguaggio (TAL) finalizzato all\u27acquisizione di terminologia specialistica a partire da corpora di testi di dominio. La metodologia qui presentata prospetta una possibile soluzione alla principale difficolt? nel processo di estrazione terminologica automatica, ovvero l\u27acquisizione di unit? terminologiche rilevanti per il dominio settoriale di acquisizione che siano distinte dalle unit? che appartengono al lessico comune di una lingua. Tale difficolt? ? dovuta principalmente alla stretta relazione che c\u27? tra lessico settoriale e lessico comune

Investigating Fine Temporal Dynamics of Prosodic and Lexical Accommodation

Conversational interaction is a dynamic activity in which participants engage in the construction of meaning and in establishing and maintaining social relationships. Lexical and prosodic accommodation have been observed in many studies as contributing importantly to these dimensions of social interaction. However, while previous works have considered accommodation mechanisms at global levels (for whole conversations, halves and thirds of conversations), this work investigates their evolution through repeated analysis at time intervals of increasing granularity to analyze the dynamics of alignment in a spoken language corpus. Results show that the levels of both prosodic and lexical accommodation fluctuate several times over the course of a conversation

Singling out Legal Knowledge from World Knowledge. An NLP-based approach

Ontology learning in the legal domain rises the well-known problem of epistemological promiscuity between legal entities and regulated domain instances. In this paper, we propose a new term extraction approach specifically aimed at tackling such a problem through the acquisition of a term glossary where legal terms, expressing legal concepts, and domain terms, providing a description of the regulated world knowledge, are automatically singled out. The proposed approach has been tested with promising results on a corpus of Italian European legal texts regulating the environmental domain

Contrastive filtering of domain specific multi-word terms from different types of corpora

In this paper we tackle the challenging task of Multi-word term (MWT) extraction from different types of specialized corpora. Contrastive filtering of previously extracted MWTs results in a considerable increment of acquired domain specific terms

Divergences in insulin resistance between the different phenotypes of the polycystic ovary syndrome

Context/Objective: Current diagnostic criteria for polycystic ovary syndrome (PCOS) have generated distinct PCOS phenotypes, based on the different combinations of diagnostic features found in each patient. Our aim was to assess whether either each single diagnostic feature or their combinations into the PCOS phenotypes may predict insulin resistance in these women. Patients/Design: A total of 137 consecutive Caucasian women with PCOS, diagnosed by the Rotterdam criteria, underwent accurate assessment of diagnostic and metabolic features. Insulin sensitivity was measured by the glucose clamp technique. Results: Among women with PCOS, 84.7% had hyperandrogenism, 84.7% had chronic oligoanovulation, and 89% had polycystic ovaries. According to the individual combinations of these features, 69.4% of women had the classic phenotype, 15.3% had the ovulatory phenotype, and 15.3% had the normoandrogenic phenotype. Most subjects (71.4%) were insulin resistant. However, insulin resistance frequency differed among phenotypes, being 80.4%, 65.0%, and 38.1%, respectively, in the 3 subgroups (P < .001). Although none of the PCOS diagnostic features per se was associated with the impairment in insulin action, after adjustment for covariates, the classic phenotype and, to a lesser extent, the ovulatory phenotype were independently associated with insulin resistance, whereas the normoandrogenic phenotype was not. Metabolic syndrome frequency was also different among phenotypes (P = .030). Conclusions: There is a scale of metabolic risk among women with PCOS. Although no single diagnostic features of PCOS are independently associated with insulin resistance, their combinations, which define PCOS phenotypes, may allow physicians to establish which women should undergo metabolic screening. In metabolic terms, women belonging to the normoandrogenic phenotype behave as a separate group