Terminology and Knowledge Representation. Italian Linguistic Resources for the Archaeological Domain

Knowledge representation is heavily based on using terminology, due to the fact that many terms have precise meanings in a specific domain but not in others. As a consequence, terms becomes unambiguous and clear, and at last, being useful for conceptualizations, are used as a starting point for formalizations. Starting from an analysis of problems in existing dictionaries, in this paper we present formalized Italian Linguistic Resources (LRs) for the Archaeological domain, in which we integrate/couple formal ontology classes and properties into/to electronic dictionary entries, using a standardized conceptual reference model. We also add Linguistic Linked Open Data (LLOD) references in order to guarantee the interoperability between linguistic and language resources, and therefore to represent knowledge

From Linguistic Resources to Ontology-Aware Terminologies: Minding the Representation Gap

Terminological resources have proven crucial in many applications ranging from Computer-Aided Translation tools to authoring software and multilingual and cross-lingual information retrieval systems. Nonetheless, with the exception of a few felicitous examples, such as the IATE (Interactive Terminology for Europe) Termbank, many terminological resources are not available in standard formats, such as Term Base eXchange (TBX), thus preventing their sharing and reuse. Yet, these terminologies could be improved associating the correspondent ontology-based information. The research described in the present contribution demonstrates the process and the methodologies adopted in the automatic conversion into TBX of such type of resources, together with their semantic enrichment based on the formalization of ontological information into terminologies. We present a proof-of-concept using the Italian Linguistic Resource for the Archaeological domain (developed according to Thesauri and Guidelines of the Italian Central Institute for the Catalogue and Documentation). Further, we introduce the conversion tool developed to support the process of creating ontology-aware terminologies for improving interoperability and sharing of existing language technologies and data set

Semi-automatic Parsing for Web Knowledge Extraction through Semantic Annotation

Parsing Web information, namely parsing content to find relevant documents on the basis of a user’s query, represents a crucial step to guarantee fast and accurate Information Retrieval (IR). Generally, an automated approach to such task is considered faster and cheaper than manual systems. Nevertheless, results do not seem have a high level of accuracy, indeed, as also Hjorland (2007) states, using stochastic algorithms entails: • Low precision due to the indexing of common Atomic Linguistic Units (ALUs) or sentences. • Low recall caused by the presence of synonyms. • Generic results arising from the use of too broad or too narrow terms. Usually IR systems are based on invert text index, namely an index data structure storing a mapping from content to its locations in a database file, or in a document or a set of documents. In this paper we propose a system, by means of which we will develop a search engine able to process online documents, starting from a natural language query, and to return information to users. The proposed approach, based on the Lexicon-Grammar (LG) framework and its language formalization methodologies, aims at integrating a semantic annotation process for both query analysis and document retrieval

An Ontology-Based Method for Extracting and Classifying Domain-Specific Compositional Nominal Compounds

In this paper, we present our preliminary study on an ontology-based method to extract and classify compositional nominal compounds in specific domains of knowledge. This method is based on the assumption that, applying a conceptual model to represent knowledge domain, it is possible to improve the extraction and classification of lexicon occurrences for that domain in a semi-automatic way. We explore the possibility of extracting and classifying a specific construction type (nominal compounds) spanning a specific domain (Cultural Heritage) and a specific language (Italian)

English as a Lingua Franca for Tourism: A Pragmatic Study in the Italian Context

This thesis is a pragmatic study of English as a Lingua Franca (ELF) communication in the special language domain of tourism. It explores overt, covert, and translanguaging practices to define how they foster communicative functions. Furthermore, the multiculturality of the research community object of the study will provide evidence of an original human cluster defined as an intercommunicating group of speakers (IGS). Capturing their stance-taking towards English as a Lingua Franca use will contribute to clarifying its iconic social meaning (Coupland 2007). The study adopts an ethnographic perspective to exemplify the dynamic nature of negotiation in language interaction and the power and cultural relations behind it. Furthermore, it combines the Ethnography of Communication with a microanalytic approach - Conversation Analysis. The triangulation of data deriving from an emic point of observation with an etic one detailed the speakers’ multilingual complex and expanded linguistic repertoire (Cogo 2012). It has also acknowledged their attitudes and orientations towards ELF communication, including the central aspects of stance-taking. In detail, my original data includes naturally occurring conversations among the 22 participants in the tour, comprising specialist tourist staff operators of different ages and educational backgrounds and non-expert visitors. The analysis was supported by interviews and questionnaire surveys conducted among participants (for their transcriptions and detailed analysis, see Parise 2022). In conclusion, this investigation explores ELF communication in an Italian tourism context to support Jenkins’s (2015) multilingual view of ELF communication. Conceivably, it will provide evidence of the strategic and dynamical use of speakers’ multilingual repertoires used as pragmatic strategies (i.e., the pedagogical function, the interpersonal function, the interpreting function) to accomplish complex social and cognitive activities in the Italian Tourist Industry. Furthermore, the investigation longitudinal participant-observation perspective allowed to define the participants as an intercommunicating group of speakers (IGS) since stabler than a TIG (transient international group)1 (see Pitzl 2016a: 25) or an example of TMC (Transient Multilingual Communities)2 (see Mortensen and Hazel 2017: 256), but more transient than a CoP in Wenger’s sense (1998). Finally, their stance observation will contribute to sociolinguistic theory investigating individual speaker/group dynamics

Knowledge Management and Cultural Heritage Repositories. Cross-Lingual Information Retrieval Strategies

In the last years important initiatives, like the development of the European Library and Europeana, aim to increase the availability of cultural content from various types of providers and institutions. The accessibility to these resources requires the development of environments which allow both to manage multilingual complexity and to preserve the semantic interoperability. The creation of Natural Language Processing (NLP) applications is finalized to the achievement of CrossLingual Information Retrieval (CLIR). This paper presents an ongoing research on language processing based on the LexiconGrammar (LG) approach with the goal of improving knowledge management in the Cultural Heritage repositories. The proposed framework aims to guarantee interoperability between multilingual systems in order to overcome crucial issues like cross-language and cross-collection retrieval. Indeed, the LG methodology tries to overcome the shortcomings of statistical approaches as in Google Translate or Bing by Microsoft concerning Multi-Word Unit (MWU) processing in queries, where the lack of linguistic context represents a serious obstacle to disambiguation. In particular, translations concerning specific domains, as it is has been widely recognized, is unambiguous since the meanings of terms are mono-referential and the type of relation that links a given term to its equivalent in a foreign language is biunivocal, i.e. a one-to-one coupling which causes this relation to be exclusive and reversible. Ontologies are used in CLIR and are considered by several scholars a promising research area to improve the effectiveness of Information Extraction (IE) techniques particularly for technical-domain queries. Therefore, we present a methodological framework which allows to map both the data and the metadata among the language-specific ont

Formal Linguistic Models and Knowledge Processing. A Structuralist Approach to Rule-Based Ontology Learning and Population

2013 - 2014The main aim of this research is to propose a structuralist approach for knowledge processing by means of ontology learning and population, achieved starting from unstructured and structured texts. The method suggested includes distributional semantic approaches and NL formalization theories, in order to develop a framework, which relies upon deep linguistic analysis... [edited by author]XIII n.s