Raquel Hervás


2020

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Proceedings of the Workshop on Intelligent Information Processing and Natural Language Generation
Daniel Sánchez | Raquel Hervás | Albert Gatt
Proceedings of the Workshop on Intelligent Information Processing and Natural Language Generation

2018

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Adapting Descriptions of People to the Point of View of a Moving Observer
Gonzalo Méndez | Raquel Hervás | Pablo Gervás | Ricardo de la Rosa | Daniel Ruiz
Proceedings of the 11th International Conference on Natural Language Generation

This paper addresses the task of generating descriptions of people for an observer that is moving within a scene. As the observer moves, the descriptions of the people around him also change. A referring expression generation algorithm adapted to this task needs to continuously monitor the changes in the field of view of the observer, his relative position to the people being described, and the relative position of these people to any landmarks around them, and to take these changes into account in the referring expressions generated. This task presents two advantages: many of the mechanisms already available for static contexts may be applied with small adaptations, and it introduces the concept of changing conditions into the task of referring expression generation. In this paper we describe the design of an algorithm that takes these aspects into account in order to create descriptions of people within a 3D virtual environment. The evaluation of this algorithm has shown that, by changing the descriptions in real time according to the observers point of view, they are able to identify the described person quickly and effectively.

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Proceedings of the 3rd Workshop on Computational Creativity in Natural Language Generation (CC-NLG 2018)
Hugo Gonçalo Oliveira | Ben Burtenshaw | Raquel Hervás
Proceedings of the 3rd Workshop on Computational Creativity in Natural Language Generation (CC-NLG 2018)

2017

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Exploring the Behavior of Classic REG Algorithms in the Description of Characters in 3D Images
Gonzalo Méndez | Raquel Hervás | Susana Bautista | Adrián Rabadán | Teresa Rodríguez
Proceedings of the 10th International Conference on Natural Language Generation

Describing people and characters can be very useful in different contexts, such as computational narrative or image description for the visually impaired. However, a review of the existing literature shows that the automatic generation of people descriptions has not received much attention. Our work focuses on the description of people in snapshots from a 3D environment. First, we have conducted a survey to identify the way in which people describe other people under different conditions. We have used the information extracted from this survey to design several Referring Expression Generation algorithms which produce similar results. We have evaluated these algorithms with users in order to identify which ones generate the best description for specific characters in different situations. The evaluation has shown that, in order to generate good descriptions, a combination of different algorithms has to be used depending on the features and situation of the person to be described.

2016

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Improving Information Extraction from Wikipedia Texts using Basic English
Teresa Rodríguez-Ferreira | Adrián Rabadán | Raquel Hervás | Alberto Díaz
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

The aim of this paper is to study the effect that the use of Basic English versus common English has on information extraction from online resources. The amount of online information available to the public grows exponentially, and is potentially an excellent resource for information extraction. The problem is that this information often comes in an unstructured format, such as plain text. In order to retrieve knowledge from this type of text, it must first be analysed to find the relevant details, and the nature of the language used can greatly impact the quality of the extracted information. In this paper, we compare triplets that represent definitions or properties of concepts obtained from three online collaborative resources (English Wikipedia, Simple English Wikipedia and Simple English Wiktionary) and study the differences in the results when Basic English is used instead of common English. The results show that resources written in Basic English produce less quantity of triplets, but with higher quality.

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Riddle Generation using Word Associations
Paloma Galván | Virginia Francisco | Raquel Hervás | Gonzalo Méndez
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

In knowledge bases where concepts have associated properties, there is a large amount of comparative information that is implicitly encoded in the values of the properties these concepts share. Although there have been previous approaches to generating riddles, none of them seem to take advantage of structured information stored in knowledge bases such as Thesaurus Rex, which organizes concepts according to the fine grained ad-hoc categories they are placed into by speakers in everyday language, along with associated properties or modifiers. Taking advantage of these shared properties, we have developed a riddle generator that creates riddles about concepts represented as common nouns. The base of these riddles are comparisons between the target concept and other entities that share some of its properties. In this paper, we describe the process we have followed to generate the riddles starting from the target concept and we show the results of the first evaluation we have carried out to test the quality of the resulting riddles.

2013

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A System for the Simplification of Numerical Expressions at Different Levels of Understandability
Susana Bautista | Raquel Hervás | Pablo Gervás | Richard Power | Sandra Williams
Proceedings of the Workshop on Natural Language Processing for Improving Textual Accessibility

2011

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Experimental Identification of the Use of Hedges in the Simplification of Numerical Expressions
Susana Bautista | Raquel Hervás | Pablo Gervás | Richard Power | Sandra Williams
Proceedings of the Second Workshop on Speech and Language Processing for Assistive Technologies

2010

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Integration of Linguistic Markup into Semantic Models of Folk Narratives: The Fairy Tale Use Case
Piroska Lendvai | Thierry Declerck | Sándor Darányi | Pablo Gervás | Raquel Hervás | Scott Malec | Federico Peinado
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

Propp's influential structural analysis of fairy tales created a powerful schema for representing storylines in terms of character functions, which is directly exploitable for computational semantic analysis, and procedural generation of stories of this genre. We tackle two resources that draw on the Proppian model - one formalizes it as a semantic markup scheme and the other as an ontology -, both lacking linguistic phenomena explicitly represented in them. The need for integrating linguistic information into structured semantic resources is motivated by the emergence of suitable standards that facilitate this, as well as the benefits such joint representation would create for transdisciplinary research across Digital Humanities, Computational Linguistics, and Artificial Intelligence.

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The Prevalence of Descriptive Referring Expressions in News and Narrative
Raquel Hervás | Mark Finlayson
Proceedings of the ACL 2010 Conference Short Papers

2009

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A Model for Human Readable Instruction Generation Using Level-Based Discourse Planning and Dynamic Inference of Attributes
Daniel Dionne | Salvador de la Puente | Carlos León | Pablo Gervás | Raquel Hervás
Proceedings of the 12th European Workshop on Natural Language Generation (ENLG 2009)

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Evolutionary and Case-Based Approaches to REG: NIL-UCM-EvoTAP, NIL-UCM-ValuesCBR and NIL-UCM-EvoCBR
Raquel Hervás | Pablo Gervás
Proceedings of the 12th European Workshop on Natural Language Generation (ENLG 2009)

2008

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Degree of Abstraction in Referring Expression Generation and its Relation with the Construction of the Contrast Set
Raquel Hervás | Pablo Gervás
Proceedings of the Fifth International Natural Language Generation Conference

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NIL-UCM: Most-Frequent-Value-First Attribute Selection and Best-Scoring-Choice Realization
Pablo Gervás | Raquel Hervás | Carlos León
Proceedings of the Fifth International Natural Language Generation Conference

2007

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NIL: attribute selection for matching the task corpus using relative attribute groupings obtained from the test data
Raquel Hervás | Pablo Gervás
Proceedings of the Workshop on Using corpora for natural language generation

2005

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An Evolutionary Approach to Referring Expression Generation and Aggregation
Raquel Hervás | Pablo Gervás
Proceedings of the Tenth European Workshop on Natural Language Generation (ENLG-05)