Abstract
In this paper, we describe an end-to-end system that automatically extracts RDF triples describing entity relations and properties from unstructured text. This system is based on a pipeline of text processing modules that includes a semantic parser and a coreference solver. By using coreference chains, we group entity actions and properties described in different sentences and convert them
into entity triples. We applied our system to over 114,000 Wikipedia articles and we could extract more than 1,000,000 triples. Using an ontology-mapping system that we bootstrapped using existing DBpedia triples, we mapped 189,000 extracted triples onto the DBpedia namespace. These extracted entities are availableonline in the N-Triple format. 1
1 http://semantica.cs.lth.se/
into entity triples. We applied our system to over 114,000 Wikipedia articles and we could extract more than 1,000,000 triples. Using an ontology-mapping system that we bootstrapped using existing DBpedia triples, we mapped 189,000 extracted triples onto the DBpedia namespace. These extracted entities are availableonline in the N-Triple format. 1
1 http://semantica.cs.lth.se/
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the Web of Linked Entities Workshop in conjuction with the 11th International Semantic Web Conference (ISWC 2012) |
| Publisher | CEUR-WS |
| Pages | 58-69 |
| Publication status | Published - 2012 |
| Event | The Web of Linked Entities Workshop (WoLE 2012) - Boston, United States Duration: 2012 Nov 11 → … |
Publication series
| Name | |
|---|---|
| ISSN (Print) | 1613-0073 |
Conference
| Conference | The Web of Linked Entities Workshop (WoLE 2012) |
|---|---|
| Country/Territory | United States |
| City | Boston |
| Period | 2012/11/11 → … |
Subject classification (UKÄ)
- Computer Sciences