In this paper we describe an ontology-driven system that performs relation extraction over textual data. The system exploits expert knowledge of the domain, including lexical resources, in the form of an ontology to drive the extraction of patterns using manually annotated texts. Such patterns are then applied in order to identify candidates for relation extraction. Paired with basic, reliable named-entity-level text annotation, this results in the discovery of relations among entities in Italian newspaper articles. In the paper, we describe the system and measure its performance.
Ontology-Driven Relation Extraction by Pattern Discovery
A Bellandi;
2010
Abstract
In this paper we describe an ontology-driven system that performs relation extraction over textual data. The system exploits expert knowledge of the domain, including lexical resources, in the form of an ontology to drive the extraction of patterns using manually annotated texts. Such patterns are then applied in order to identify candidates for relation extraction. Paired with basic, reliable named-entity-level text annotation, this results in the discovery of relations among entities in Italian newspaper articles. In the paper, we describe the system and measure its performance.| Campo DC | Valore | Lingua |
|---|---|---|
| dc.authority.people | A Bellandi | it |
| dc.authority.people | S Nasoni | it |
| dc.authority.people | A Tommasi | it |
| dc.authority.people | C Zavattari | 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 | 2024/02/20 11:09:01 | - |
| dc.date.available | 2024/02/20 11:09:01 | - |
| dc.date.issued | 2010 | - |
| dc.description.abstracteng | In this paper we describe an ontology-driven system that performs relation extraction over textual data. The system exploits expert knowledge of the domain, including lexical resources, in the form of an ontology to drive the extraction of patterns using manually annotated texts. Such patterns are then applied in order to identify candidates for relation extraction. Paired with basic, reliable named-entity-level text annotation, this results in the discovery of relations among entities in Italian newspaper articles. In the paper, we describe the system and measure its performance. | - |
| dc.description.affiliations | Department of Computer Science University of Pisa - Italy, Metaware S.p.A. Pisa - Italy, Metaware S.p.A. Pisa - Italy, Metaware S.p.A. Pisa - Italy | - |
| dc.description.allpeople | A. Bellandi; S. Nasoni; A. Tommasi; C. Zavattari | - |
| dc.description.allpeopleoriginal | A. Bellandi, S. Nasoni, A. Tommasi, C. Zavattari | - |
| dc.description.fulltext | none | en |
| dc.description.numberofauthors | 1 | - |
| dc.identifier.uri | https://hdl.handle.net/20.500.14243/265111 | - |
| dc.language.iso | eng | - |
| dc.relation.conferencedate | 10-15/02/2010 | - |
| dc.relation.conferencename | Second IEEE International Conference on Information, Process, and Knowledge Management. 2010 | - |
| dc.relation.conferenceplace | Antilles | - |
| dc.title | Ontology-Driven Relation Extraction by Pattern Discovery | 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.ugov.descaux1 | 272217 | - |
| iris.orcid.lastModifiedDate | 2024/03/02 05:15:12 | * |
| iris.orcid.lastModifiedMillisecond | 1709352912033 | * |
| iris.sitodocente.maxattempts | 1 | - |
| Appare nelle tipologie: | 04.01 Contributo in Atti di convegno | |
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