This paper presents a Lexicon-Grammar based method for automatic extraction of spatial relations from Italian non-structured data. We used the software Nooj to build sophisticated local grammars and electronic dictionaries associated with the lexicon-grammar classes of the Italian intransitive spatial verbs (i.e. 234 verbal entries) and we applied them to the Italian text Il Codice da Vinci ('The Da Vinci Code', by Dan Brown) in order to parse the spatial predicate-arguments structures. In addition, Nooj allowed us to automatically annotate (in XML format) the words (or the sequence of words) that in each sentence (S) of the text play the 'spatial roles' of Figure (F), Motion (M) and Ground (G). Finally the results of the experiment and the evaluation of this method will be discussed.
A Linguistic-Based Method for Automatically Extracting Spatial Relations from Large Non-Structured Data
ELIA, AnnibaleConceptualization
;GUGLIELMO, DANIELAWriting – Original Draft Preparation
;PELOSI, SERENAFormal Analysis
;MAISTO, ALESSANDROValidation
2013-01-01
Abstract
This paper presents a Lexicon-Grammar based method for automatic extraction of spatial relations from Italian non-structured data. We used the software Nooj to build sophisticated local grammars and electronic dictionaries associated with the lexicon-grammar classes of the Italian intransitive spatial verbs (i.e. 234 verbal entries) and we applied them to the Italian text Il Codice da Vinci ('The Da Vinci Code', by Dan Brown) in order to parse the spatial predicate-arguments structures. In addition, Nooj allowed us to automatically annotate (in XML format) the words (or the sequence of words) that in each sentence (S) of the text play the 'spatial roles' of Figure (F), Motion (M) and Ground (G). Finally the results of the experiment and the evaluation of this method will be discussed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.