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Erschienen in:
Reducing the Degradation of Sentiment Analysis for Text Collections Spread over a Period of Time Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

Discovering Relational Phrases for Qualia Roles Through Open Information Extraction

verfasst von : Giovanni Siragusa, Valentina Leone, Luigi Di Caro, Claudio Schifanella

Erschienen in: Knowledge Engineering and Semantic Web

Verlag: Springer International Publishing

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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.

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Vorheriges Kapitel The Algorithm of Modelling and Analysis of Latent Semantic Relations: Linear Algebra vs. Probabilistic Topic Models
Nächstes Kapitel Probabilistic Topic Modelling for Controlled Snowball Sampling in Citation Network Collection
Fußnoten
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.
 
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.
 
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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Metadaten
Titel
Discovering Relational Phrases for Qualia Roles Through Open Information Extraction
verfasst von
Giovanni Siragusa
Valentina Leone
Luigi Di Caro
Claudio Schifanella
Copyright-Jahr
2017
Buch
Knowledge Engineering and Semantic Web

Print ISBN: 978-3-319-69547-1

Electronic ISBN: 978-3-319-69548-8

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-69548-8_6

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