Abstract
The concurrent growth of the Document Web and the Data Web demands accurate information extraction tools to bridge the gap between the two. In particular, the extraction of knowledge on real-world entities is indispensable to populate knowledge bases on the Web of Data. Here, we focus on the recognition of types for entities to populate knowledge bases and enable subsequent knowledge extraction steps. We present CETUS, a baseline approach to entity type extraction. CETUS is based on a three-step pipeline comprising (i) offline, knowledge-driven type pattern extraction from natural-language corpora based on grammar-rules, (ii) an analysis of input text to extract types and (iii) the mapping of the extracted type evidence to a subset of the DOLCE+DnS Ultra Lite ontology classes. We implement and compare two approaches for the third step using the YAGO ontology as well as the FOX entity recognition tool.
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Notes
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See http://stlab.istc.cnr.it/stlab/WikipediaOntology/. Throughout this paper, we use the prefix dul for types of this ontology.
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Abbreviations in Listing 1.1: ADJ = adjective, CD = cardinal number.
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The complete grammar can be found in the projects source code repository.
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The rdfs prefix stands for http://www.w3.org/2000/01/rdf-schema while the prefix ex could stay for every user defined vocabulary, e.g., http://example.com/.
- 9.
This mapping can be found inside the git repository of the project at https://github.com/AKSW/Cetus/blob/master/DOLCE_YAGO_links.nt.
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Throughout this paper, we use the prefix yago for http://yago-knowledge.org/resource/.
- 11.
The results of the challenge can be found at https://github.com/anuzzolese/oke-challenge#results.
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Acknowledgements
This work has been supported by the FP7 project GeoKnow (GA No. 318159) and the BMWI Project SAKE (Project No. 01MD15006E).
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Röder, M., Usbeck, R., Speck, R., Ngomo, AC.N. (2015). CETUS – A Baseline Approach to Type Extraction. In: Gandon, F., Cabrio, E., Stankovic, M., Zimmermann, A. (eds) Semantic Web Evaluation Challenges. SemWebEval 2015. Communications in Computer and Information Science, vol 548. Springer, Cham. https://doi.org/10.1007/978-3-319-25518-7_2
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