The paper reports on methodology and preliminary results ofa case study in automatically extracting ontological knowledgefrom Italian legislative texts in the environmental domain. Weuse a fully-implemented ontology learning system (T2K) thatincludes a battery of tools for Natural Language Processing(NLP), statistical text analysis and machine language learn-ing. Tools are dynamically integrated to provide an incremen-tal representation of the content of vast repositories of unstruc-tured documents. Evaluated results, however preliminary, arevery encouraging, showing the great potential of NLP-poweredincremental systems like T2K for accurate large-scale semi-automatic extraction of legal ontologies.
Acquiring Legal Ontologies from Domain-specific Texts
Dell'Orletta F;Montemagni S;Marchi S;Pirrelli V;Venturi G
2008
Abstract
The paper reports on methodology and preliminary results ofa case study in automatically extracting ontological knowledgefrom Italian legislative texts in the environmental domain. Weuse a fully-implemented ontology learning system (T2K) thatincludes a battery of tools for Natural Language Processing(NLP), statistical text analysis and machine language learn-ing. Tools are dynamically integrated to provide an incremen-tal representation of the content of vast repositories of unstruc-tured documents. Evaluated results, however preliminary, arevery encouraging, showing the great potential of NLP-poweredincremental 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 | Dell'Orletta F | it |
| dc.authority.people | Lenci A | it |
| dc.authority.people | Montemagni S | it |
| dc.authority.people | Marchi 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 19:37:29 | - |
| dc.date.available | 2024/02/19 19:37:29 | - |
| dc.date.issued | 2008 | - |
| dc.description.abstracteng | The paper reports on methodology and preliminary results ofa case study in automatically extracting ontological knowledgefrom Italian legislative texts in the environmental domain. Weuse a fully-implemented ontology learning system (T2K) thatincludes a battery of tools for Natural Language Processing(NLP), statistical text analysis and machine language learn-ing. Tools are dynamically integrated to provide an incremen-tal representation of the content of vast repositories of unstruc-tured documents. Evaluated results, however preliminary, arevery encouraging, showing the great potential of NLP-poweredincremental systems like T2K for accurate large-scale semi-automatic extraction of legal ontologies. | - |
| dc.description.affiliations | Lenci Alessandro: Università di Pisa. | - |
| dc.description.allpeople | Dell'Orletta, F; Lenci, A; Montemagni, S; Marchi, S; Pirrelli, V; Venturi, G | - |
| dc.description.allpeopleoriginal | Dell'Orletta F.; Lenci A.; Montemagni S.; Marchi S.; Pirrelli V.; Venturi G. | - |
| dc.description.fulltext | none | en |
| dc.description.numberofauthors | 6 | - |
| dc.identifier.uri | https://hdl.handle.net/20.500.14243/65074 | - |
| dc.language.iso | eng | - |
| dc.relation.conferencedate | 28-29/02/2008 | - |
| dc.relation.conferencename | LangTech 2008 | - |
| dc.relation.conferenceplace | Roma | - |
| dc.relation.firstpage | 98 | - |
| dc.relation.lastpage | 101 | - |
| dc.relation.numberofpages | 4 | - |
| dc.subject.keywords | Ontology learning | - |
| dc.subject.keywords | Document management | - |
| dc.subject.keywords | knowledge extraction from texts | - |
| dc.subject.keywords | Natural Language Processing | - |
| dc.subject.singlekeyword | Ontology learning | * |
| dc.subject.singlekeyword | Document management | * |
| dc.subject.singlekeyword | knowledge extraction from texts | * |
| dc.subject.singlekeyword | Natural Language Processing | * |
| dc.title | Acquiring Legal Ontologies from Domain-specific Texts | 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 | No | - |
| dc.ugov.descaux1 | 84698 | - |
| iris.orcid.lastModifiedDate | 2024/04/04 13:29:10 | * |
| iris.orcid.lastModifiedMillisecond | 1712230150890 | * |
| iris.sitodocente.maxattempts | 4 | - |
| Appare nelle tipologie: | 04.01 Contributo in Atti di convegno | |
File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
