The paper reports on the methodology and preliminary results of a case study in automatically extracting ontological knowledge from Italian legislative texts. We use a fully-implemented ontology learning system (T2K) that includes a battery of tools for Natural Language Processing (NLP), statistical text analysis and machine language learning. Tools are dynamically integrated to provide an incremental representation of the content of vast repositories of unstructured documents. Evaluated results, however preliminary, show the great potential of NLP-powered incremental systems like T2K for accurate large-scale semi-automatic extraction of legal ontologies.
Ontology learning from Italian legal texts
Montemagni S;Pirrelli V;
2009
Abstract
The paper reports on the methodology and preliminary results of a case study in automatically extracting ontological knowledge from Italian legislative texts. We use a fully-implemented ontology learning system (T2K) that includes a battery of tools for Natural Language Processing (NLP), statistical text analysis and machine language learning. Tools are dynamically integrated to provide an incremental representation of the content of vast repositories of unstructured documents. Evaluated results, however preliminary, show the great potential of NLP-powered incremental systems like T2K for accurate large-scale semi-automatic extraction of legal ontologies.| Campo DC | Valore | Lingua |
|---|---|---|
| dc.authority.orgunit | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | - |
| dc.authority.people | Lenci A | it |
| dc.authority.people | Montemagni S | it |
| dc.authority.people | Pirrelli V | it |
| dc.authority.people | Giulia V | it |
| dc.collection.id.s | 8c50ea44-be95-498f-946e-7bb5bd666b7c | * |
| dc.collection.name | 02.01 Contributo in volume (Capitolo o Saggio) | * |
| dc.contributor.appartenenza | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | * |
| dc.contributor.appartenenza.mi | 918 | * |
| dc.date.accessioned | 2024/02/17 13:42:19 | - |
| dc.date.available | 2024/02/17 13:42:19 | - |
| dc.date.issued | 2009 | - |
| dc.description.abstracteng | The paper reports on the methodology and preliminary results of a case study in automatically extracting ontological knowledge from Italian legislative texts. We use a fully-implemented ontology learning system (T2K) that includes a battery of tools for Natural Language Processing (NLP), statistical text analysis and machine language learning. Tools are dynamically integrated to provide an incremental representation of the content of vast repositories of unstructured documents. Evaluated results, however preliminary, show the great potential of NLP-powered incremental systems like T2K for accurate large-scale semi-automatic extraction of legal ontologies. | - |
| dc.description.affiliations | Università di Pisa; ILC-CNR, Pisa | - |
| dc.description.allpeople | Lenci A.; Montemagni S.; Pirrelli V.; Giulia V. | - |
| dc.description.allpeopleoriginal | Lenci A.; Montemagni S.; Pirrelli V.; Giulia V. | - |
| dc.description.fulltext | none | en |
| dc.description.numberofauthors | 2 | - |
| dc.identifier.doi | 10.3233/978-1-58603-942-4-75 | - |
| dc.identifier.isbn | 978-1-58603-942-4 | - |
| dc.identifier.uri | https://hdl.handle.net/20.500.14243/134815 | - |
| dc.language.iso | eng | - |
| dc.relation.alleditors | Joost Breuker; Pompeu Casanovas; Michel C.A. Klein; Enrico Francesconi | - |
| dc.relation.firstpage | 75 | - |
| dc.relation.ispartofbook | Law, Ontologies and the Semantic Web - Channelling the Legal Information Flood | - |
| dc.relation.lastpage | 94 | - |
| dc.relation.numberofpages | 20 | - |
| dc.subject.keywords | Ontology Learning | - |
| dc.subject.keywords | document management | - |
| dc.subject.keywords | legal knowledge extraction | - |
| dc.subject.singlekeyword | Ontology Learning | * |
| dc.subject.singlekeyword | document management | * |
| dc.subject.singlekeyword | legal knowledge extraction | * |
| dc.title | Ontology learning from Italian legal texts | en |
| dc.type.driver | info:eu-repo/semantics/bookPart | - |
| dc.type.full | 02 Contributo in Volume::02.01 Contributo in volume (Capitolo o Saggio) | it |
| dc.type.miur | 268 | - |
| dc.type.referee | Sì, ma tipo non specificato | - |
| dc.ugov.descaux1 | 136465 | - |
| iris.orcid.lastModifiedDate | 2024/03/02 05:06:32 | * |
| iris.orcid.lastModifiedMillisecond | 1709352392059 | * |
| iris.scopus.extIssued | 2009 | - |
| iris.scopus.extTitle | Ontology learning from Italian legal texts | - |
| iris.sitodocente.maxattempts | 2 | - |
| iris.unpaywall.doi | 10.3233/978-1-58603-942-4-75 | * |
| iris.unpaywall.isoa | false | * |
| iris.unpaywall.journalisindoaj | false | * |
| iris.unpaywall.metadataCallLastModified | 12/12/2025 03:14:41 | - |
| iris.unpaywall.metadataCallLastModifiedMillisecond | 1765505681494 | - |
| iris.unpaywall.oastatus | closed | * |
| Appare nelle tipologie: | 02.01 Contributo in volume (Capitolo o Saggio) | |
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