Nymble: a high-performance learning name-finder
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
KIM – a semantic platform for information extraction and retrieval
Natural Language Engineering
Gimme' the context: context-driven automatic semantic annotation with C-PANKOW
WWW '05 Proceedings of the 14th international conference on World Wide Web
Combining linguistic and statistical analysis to extract relations from web documents
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
YAGO: A Large Ontology from Wikipedia and WordNet
Web Semantics: Science, Services and Agents on the World Wide Web
SOFIE: a self-organizing framework for information extraction
Proceedings of the 18th international conference on World wide web
Fuzzy Annotation of Web Data Tables Driven by a Domain Ontology
ESWC 2009 Heraklion Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications
Incremental Ontology-Based Extraction and Alignment in Semi-structured Documents
DEXA '09 Proceedings of the 20th International Conference on Database and Expert Systems Applications
DBpedia - A crystallization point for the Web of Data
Web Semantics: Science, Services and Agents on the World Wide Web
Annotating and searching web tables using entities, types and relationships
Proceedings of the VLDB Endowment
Designing and evaluating patterns for ontology enrichment from texts
EKAW'06 Proceedings of the 15th international conference on Managing Knowledge in a World of Networks
Moving beyond SameAs with PLATO: partonomy detection for linked data
Proceedings of the 23rd ACM conference on Hypertext and social media
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The Linked Open Data initiative brought more and more RDF data sources to be published on the Web. However, these data sources contain relatively little information compared to the documents available on the surface Web. Many annotation tools have been proposed in the last decade for the automatic construction and enrichment of knowledge bases. But, while noticeable advances are achieved for the extraction of concept instances, the extraction of semantic relations remains a challenging task when the structures and the vocabularies of the target documents are heterogeneous. In this paper, we propose a novel approach, called REISA, which allows to enrich RDF/OWL knowledge bases with semantic relations using semistructured documents annotated with concept instances. REISA produces weighted relation instances without exploiting lexico-syntactic or structure regularities in the documents. Neighbor domain entities in the annotated documents are used to generate the first sets of candidate relations according to the domain and range axioms defined in a domain ontology. The construction of these candidate sets relies on automated semantic controls performed with (i) the existing knowledge bases and (ii) the (inverse) functionality of the target relations. The weighting of the selected relation candidates is performed according to the neighborhood distance between the annotated domain entities in the document. Experiments on two real web datasets show that (i) REISA allows to extract semantic relationships with interesting precision values reaching 76,5% and that (ii) the weighting method is effective for ranking the relation candidates according to their precision.