Abstract
In Generative Lexicon [17], Pustejovsky defined the Qualia Structure which organizes the semantic meaning carried by nouns through four roles: formal, telic, agentive and constitutive. Despite their expressive power, to the best of our knowledge no actual NLP system uses qualia structures possibly due to the large effort needed to construct such knowledge bases. Some researchers have tried to circumvent this obstacle using lexico-syntactic patterns based on Hearst idea [11]. In this paper, we propose an Open Information Extraction method to automatically acquire a set of relational phrases from a large corpus, starting with a small set of nouns and their qualia elements. Our idea is that the relational phrases unveil the relations between the nouns and their qualia elements. We compared our method with Reverb [10], Ollie [18] and ClausIE [9] in terms of patterns quality and the relative qualia elements extraction.
The major part of this work has been carried out by the first two authors, equally. The work has been funded by the project Semantic Burst: Embodying Semantic Resources in Vector Space Models, financed by Compagnia di San Paolo.
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Notes
- 1.
Note that we have two possible cases: (argument1 = noun, argument2 = qualia element) and (argument1 = qualia element, argument2 = noun).
- 2.
An exception is ClausIE [9] which can extract pairs of the form (argument, relational phrase) and N-ary relations composed by a triple and a set of additional information.
- 3.
- 4.
We used Mate-Tools parser (http://code.google.com/p/mate-tools).
- 5.
If the term referring to the argument has an empty babelnetids attribute in the qualia structure, we consider the argument as correct.
- 6.
The resource is available at the following url: http://lcl.uniroma1.it/babelfied-wikipedia/.
- 7.
We could not manage to solve this issue with the help of the available documentation.
- 8.
In case of a missing score, we assumed it as 0.
- 9.
- 10.
In case of a missing evaluation of a qualia element, we assumed that it does not belong to the role.
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Siragusa, G., Leone, V., Di Caro, L., Schifanella, C. (2017). Discovering Relational Phrases for Qualia Roles Through Open Information Extraction. In: Różewski, P., Lange, C. (eds) Knowledge Engineering and Semantic Web. KESW 2017. Communications in Computer and Information Science, vol 786. Springer, Cham. https://doi.org/10.1007/978-3-319-69548-8_6
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