The main topic of this paper is to describe how to transform effectively the “lexical matter” of a language (not only Italian) into a formal and taxonomic morphosyntactic classification of the simple words stored and tagged inside NooJ electronic dictionaries. The ultimate goal is to build electronic dictionaries for NooJ that can be used effectively in Natural Language Processing (NLP) and Automatic Textual Analysis (ATA). To achieve this task, we will start from the following assumption: nouns inflectioncodes may prove useful not only to describe morphological behaviours and features, but also to “predict” syntactic combinations inside sentences. This means that inside NooJ finite-state automata (FSA) and transducers (FST), nouns inflection codes can account for Lexicon-Grammar (LG) co-occurrence and selection restriction rules, thus also providing for several aspects of formal semantics (FS).The method we intend to outline here can therefore become a descriptive and applicative standard, reusable for all those languages in which word inflection has a value not only morphological (as for gender, number and possibly case) but also syntactic. As is known, such a formal descriptive approach is absent in paper dictionaries, in which there is a tendency to “flatten” the morphosyntactic description of words in favour of a list of words which uses rely heavily on the linguistic competence of readers and speakers.

Morphosyntax and Semantics in the NooJ Italian Dictionary of Simple Words

Monteleone, Mario
2022-01-01

Abstract

The main topic of this paper is to describe how to transform effectively the “lexical matter” of a language (not only Italian) into a formal and taxonomic morphosyntactic classification of the simple words stored and tagged inside NooJ electronic dictionaries. The ultimate goal is to build electronic dictionaries for NooJ that can be used effectively in Natural Language Processing (NLP) and Automatic Textual Analysis (ATA). To achieve this task, we will start from the following assumption: nouns inflectioncodes may prove useful not only to describe morphological behaviours and features, but also to “predict” syntactic combinations inside sentences. This means that inside NooJ finite-state automata (FSA) and transducers (FST), nouns inflection codes can account for Lexicon-Grammar (LG) co-occurrence and selection restriction rules, thus also providing for several aspects of formal semantics (FS).The method we intend to outline here can therefore become a descriptive and applicative standard, reusable for all those languages in which word inflection has a value not only morphological (as for gender, number and possibly case) but also syntactic. As is known, such a formal descriptive approach is absent in paper dictionaries, in which there is a tendency to “flatten” the morphosyntactic description of words in favour of a list of words which uses rely heavily on the linguistic competence of readers and speakers.
2022
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4852306
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