The paper reports on the methodology and preliminary results of a case study in automatically extracting ontological knowledge from Italian legislative texts in the environmental domain. 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, are very encouraging, showing the great potential of NLP-powered incremental systems like T2K for accurate large-scale semi-automatic extraction of legal ontologies.
NLP-based ontology learning from legal texts. A case study
Montemagni S;Pirrelli V;Venturi G
2007
Abstract
The paper reports on the methodology and preliminary results of a case study in automatically extracting ontological knowledge from Italian legislative texts in the environmental domain. 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, are very encouraging, showing 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 | Venturi G | it |
| dc.collection.id.s | 71c7200a-7c5f-4e83-8d57-d3d2ba88f40d | * |
| dc.collection.name | 04.01 Contributo in Atti di convegno | * |
| dc.contributor.appartenenza | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | * |
| dc.contributor.appartenenza.mi | 918 | * |
| dc.date.accessioned | 2024/02/19 19:36:13 | - |
| dc.date.available | 2024/02/19 19:36:13 | - |
| dc.date.issued | 2007 | - |
| 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 in the environmental domain. 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, are very encouraging, showing the great potential of NLP-powered incremental systems like T2K for accurate large-scale semi-automatic extraction of legal ontologies. | - |
| dc.description.affiliations | Lenci A.: Università degli Studi di Pisa. Montemagni S., Pirrelli V., Venturi G.: ILC - Istituto di linguistica computazionale "Antonio Zampolli" | - |
| dc.description.allpeople | Lenci, A; Montemagni, S; Pirrelli, V; Venturi, G | - |
| dc.description.allpeopleoriginal | Lenci A., Montemagni S., Pirrelli V., Venturi G. | - |
| dc.description.fulltext | none | en |
| dc.description.numberofauthors | 4 | - |
| dc.identifier.uri | https://hdl.handle.net/20.500.14243/65070 | - |
| dc.language.iso | eng | - |
| dc.relation.conferencedate | 4 giugno 2007 | - |
| dc.relation.conferencename | II Workshop on Legal Ontologies and Artificial Intelligence Techniques (LOAIT'07) | - |
| dc.relation.conferenceplace | Stanford | - |
| dc.relation.firstpage | 113 | - |
| dc.relation.lastpage | 129 | - |
| dc.title | NLP-based ontology learning from legal texts. A case study | en |
| dc.type.driver | info:eu-repo/semantics/conferenceObject | - |
| dc.type.full | 04 Contributo in convegno::04.01 Contributo in Atti di convegno | it |
| dc.type.miur | 273 | - |
| dc.type.referee | Sì, ma tipo non specificato | - |
| dc.ugov.descaux1 | 84693 | - |
| iris.orcid.lastModifiedDate | 2024/04/04 15:44:34 | * |
| iris.orcid.lastModifiedMillisecond | 1712238274729 | * |
| iris.scopus.extIssued | 2007 | - |
| iris.scopus.extTitle | NLP-based ontology learning from legal texts. A case study | - |
| iris.sitodocente.maxattempts | 1 | - |
| Appare nelle tipologie: | 04.01 Contributo in Atti di convegno | |
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