Abstract
Semantic annotation is fundamental to deal with large-scale lexical information, mapping the information to an enumerable set of categories over which rules and algorithms can be applied, and foundational ontology classes can be used as a formal set of categories for such tasks. A previous alignment between WordNet noun synsets and DOLCE provided a starting point for ontology-based annotation, but in NLP tasks verbs are also of substantial importance. This work presents an extension to the WordNet-DOLCE noun mapping, aligning verbs according to their links to nouns denoting perdurants, transferring to the verb the DOLCE class assigned to the noun that best represents that verb’s occurrence. To evaluate the usefulness of this resource, we implemented a foundational ontology-based semantic annotation framework, that assigns a high-level foundational category to each word or phrase in a text, and compared it to a similar annotation tool, obtaining an increase of 9.05 % in accuracy.
V.S. Silva—CNPq Fellow – Brazil.
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Notes
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Mappings available at https://goo.gl/bflXqx.
- 2.
Computed by the “conlleval” script, available at http://goo.gl/YL2IBz.
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This work is in part funded by the SSIX Horizon 2020 project (grant agreement No. 645425).
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Silva, V.S., Freitas, A., Handschuh, S. (2016). Word Tagging with Foundational Ontology Classes: Extending the WordNet-DOLCE Mapping to Verbs. In: Blomqvist, E., Ciancarini, P., Poggi, F., Vitali, F. (eds) Knowledge Engineering and Knowledge Management. EKAW 2016. Lecture Notes in Computer Science(), vol 10024. Springer, Cham. https://doi.org/10.1007/978-3-319-49004-5_38
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