Towards the Fully Automatic Merging of Lexical Resources: A Step Forward

This article reports on the results of the research done towards the fully automatically merging of lexical resources. Our main goal is to show the generality of the proposed approach, which have been previously applied to merge Spanish Subcategorization Frames lexica. In this work we extend and apply the same technique to perform the merging of morphosyntactic lexica encoded in LMF. The experiments showed that the technique is general enough to obtain good results in these two different tasks which is an important step towards performing the merging of lexical resources fully automatically.

Towards the Automatic Merging of Lexical Resources: Automatic Mapping

Lexical Resources are a critical component for Natural Language Processing applications. However, the high cost of comparing and merging different resources has been a bottleneck to have richer resources with a broad range of potential uses for a significant number of languages.With the objective of reducing cost byeliminating human intervention, we present a new method for automating the merging of resources,with special emphasis in what we call the mapping step. This mapping step, which converts the resources into a common format that allows latter the merging, is usually performed with huge manual effort and thus makes the whole process very costly. Thus, we propose a method to perform this mapping fully automatically. To test our method, we have addressed the merging of two verb subcategorization frame lexica for Spanish, The resultsachieved, that almost replicate human work, demonstrate the feasibility of the approach.

A Method Towards the Fully Automatic Merging of Lexical Resources

Lexical Resources are a critical component for Natural Language Processing applications. However, the high cost of comparing and merging different resources has been a bottleneck to obtain richer resources and a broader range of potential uses for a significant number of languages. With the objective of reducing cost by eliminating human intervention, we present a new method towards the automatic merging of resources. This method includes both, the automatic mapping of resources involved to a common format and merging them, once in this format. This paper presents how we have addressed the merging of two verb subcategorization frame lexica for Spanish, but our method will be extended to cover other types of Lexical Resources. The achieved results, that almost replicate human work, demonstrate the feasibility of the approach.

Interchanging lexical resources on the Semantic Web

Lexica and terminology databases play a vital role in many NLP applications, but currently most such resources are published in application-specific formats, or with custom access interfaces, leading to the problem that much of this data is in ‘‘data silos’’ and hence difficult to access. The Semantic Web and in particular the Linked Data initiative provide effective solutions to this problem, as well as possibilities for data reuse by inter-lexicon linking, and incorporation of data categories by dereferencable URIs. The Semantic Web focuses on the use of ontologies to describe semantics on the Web, but currently there is no standard for providing complex lexical information for such ontologies and for describing the relationship between the lexicon and the ontology. We present our model, lemon, which aims to address these gaps

Automatic Creation of Lexical Resources for an Interlingua-based System

The Universal Networking Language (UNL) is an interlingua designed to be the base of several natural language processing systems aiming to support multilinguality in internet. One of the main components of the language is the dictionary of Universal Words (UWs), which links the vocabularies of the different languages involved in the project. As any NLP system, coverage and accuracy in its lexical resources are crucial for the development of the system. In this paper, the authors describes how a large coverage UWs dictionary was automatically created, based on an existent and well known resource like the English WordNet. Other aspects like implementation details and the evaluation of the final UW set are also depicted.

Language Resources – a Part of World Cultural Heritage

This article briefly reviews multilingual language resources for Bulgarian, developed in the frame of some international projects: the first-ever annotated Bulgarian MTE digital lexical resources, Bulgarian-Polish corpus, Bulgarian-Slovak parallel and aligned corpus, and Bulgarian-Polish-Lithuanian corpus. These resources are valuable multilingual dataset for language engineering research and development for Bulgarian language. The multilingual corpora are large repositories of language data with an important role in preserving and supporting the world's cultural heritage, because the natural language is an outstanding part of the human cultural values and collective memory, and a bridge between cultures.

Frame detection over the semantic web

In the past, research in ontology learning from text has mainly focused on entity recognition, taxonomy induction and relation extraction. In this work we approach a challenging research issue: detecting semantic frames from texts and using them to encode web ontologies. We exploit a new generation Natural Language Processing technology for frame detection, and we enrich the frames acquired so far with argument restrictions provided by a super-sense tagger and domain specializations. The results are encoded according to a Linguistic MetaModel, which allows a complete translation of lexical resources and data acquired from text, enabling custom transformations of the enriched frames into modular ontology components.

Annotation syntaxico-sémantique des actants en corpus spécialisé

L’annotation en rôles sémantiques est une tâche qui permet d’attribuer des étiquettes de rôles telles que Agent, Patient, Instrument, Lieu, Destination etc. aux différents participants actants ou circonstants (arguments ou adjoints) d’une lexie prédicative. Cette tâche nécessite des ressources lexicales riches ou des corpus importants contenant des phrases annotées manuellement par des linguistes sur lesquels peuvent s’appuyer certaines approches d’automatisation (statistiques ou apprentissage machine). Les travaux antérieurs dans ce domaine ont porté essentiellement sur la langue anglaise qui dispose de ressources riches, telles que PropBank, VerbNet et FrameNet, qui ont servi à alimenter les systèmes d’annotation automatisés. L’annotation dans d’autres langues, pour lesquelles on ne dispose pas d’un corpus annoté manuellement, repose souvent sur le FrameNet anglais. Une ressource telle que FrameNet de l’anglais est plus que nécessaire pour les systèmes d’annotation automatisé et l’annotation manuelle de milliers de phrases par des linguistes est une tâche fastidieuse et exigeante en temps. Nous avons proposé dans cette thèse un système automatique pour aider les linguistes dans cette tâche qui pourraient alors se limiter à la validation des annotations proposées par le système. Dans notre travail, nous ne considérons que les verbes qui sont plus susceptibles que les noms d’être accompagnés par des actants réalisés dans les phrases. Ces verbes concernent les termes de spécialité d’informatique et d’Internet (ex. accéder, configurer, naviguer, télécharger) dont la structure actancielle est enrichie manuellement par des rôles sémantiques. La structure actancielle des lexies verbales est décrite selon les principes de la Lexicologie Explicative et Combinatoire, LEC de Mel’čuk et fait appel partiellement (en ce qui concerne les rôles sémantiques) à la notion de Frame Element tel que décrit dans la théorie Frame Semantics (FS) de Fillmore. Ces deux théories ont ceci de commun qu’elles mènent toutes les deux à la construction de dictionnaires différents de ceux issus des approches traditionnelles. Les lexies verbales d’informatique et d’Internet qui ont été annotées manuellement dans plusieurs contextes constituent notre corpus spécialisé. Notre système qui attribue automatiquement des rôles sémantiques aux actants est basé sur des règles ou classificateurs entraînés sur plus de 2300 contextes. Nous sommes limités à une liste de rôles restreinte car certains rôles dans notre corpus n’ont pas assez d’exemples annotés manuellement. Dans notre système, nous n’avons traité que les rôles Patient, Agent et Destination dont le nombre d’exemple est supérieur à 300. Nous avons crée une classe que nous avons nommé Autre où nous avons rassemblé les autres rôles dont le nombre d’exemples annotés est inférieur à 100. Nous avons subdivisé la tâche d’annotation en sous-tâches : identifier les participants actants et circonstants et attribuer des rôles sémantiques uniquement aux actants qui contribuent au sens de la lexie verbale. Nous avons soumis les phrases de notre corpus à l’analyseur syntaxique Syntex afin d’extraire les informations syntaxiques qui décrivent les différents participants d’une lexie verbale dans une phrase. Ces informations ont servi de traits (features) dans notre modèle d’apprentissage. Nous avons proposé deux techniques pour l’identification des participants : une technique à base de règles où nous avons extrait une trentaine de règles et une autre technique basée sur l’apprentissage machine. Ces mêmes techniques ont été utilisées pour la tâche de distinguer les actants des circonstants. Nous avons proposé pour la tâche d’attribuer des rôles sémantiques aux actants, une méthode de partitionnement (clustering) semi supervisé des instances que nous avons comparée à la méthode de classification de rôles sémantiques. Nous avons utilisé CHAMÉLÉON, un algorithme hiérarchique ascendant.

Criteria for the validation of specialized verb equivalents : application in bilingual terminography

Multilingual terminological resources do not always include valid equivalents of legal terms for two main reasons. Firstly, legal systems can differ from one language community to another and even from one country to another because each has its own history and traditions. As a result, the non-isomorphism between legal and linguistic systems may render the identification of equivalents a particularly challenging task. Secondly, by focusing primarily on the definition of equivalence, a notion widely discussed in translation but not in terminology, the literature does not offer solid and systematic methodologies for assigning terminological equivalents. As a result, there is a lack of criteria to guide both terminologists and translators in the search and validation of equivalent terms. This problem is even more evident in the case of predicative units, such as verbs. Although some terminologists (L‘Homme 1998; Lerat 2002; Lorente 2007) have worked on specialized verbs, terminological equivalence between units that belong to this part of speech would benefit from a thorough study. By proposing a novel methodology to assign the equivalents of specialized verbs, this research aims at defining validation criteria for this kind of predicative units, so as to contribute to a better understanding of the phenomenon of terminological equivalence as well as to the development of multilingual terminography in general, and to the development of legal terminography, in particular. The study uses a Portuguese-English comparable corpus that consists of a single genre of texts, i.e. Supreme Court judgments, from which 100 Portuguese and 100 English specialized verbs were selected. The description of the verbs is based on the theory of Frame Semantics (Fillmore 1976, 1977, 1982, 1985; Fillmore and Atkins 1992), on the FrameNet methodology (Ruppenhofer et al. 2010), as well as on the methodology for compiling specialized lexical resources, such as DiCoInfo (L‘Homme 2008), developed in the Observatoire de linguistique Sens-Texte at the Université de Montréal. The research reviews contributions that have adopted the same theoretical and methodological framework to the compilation of lexical resources and proposes adaptations to the specific objectives of the project. In contrast to the top-down approach adopted by FrameNet lexicographers, the approach described here is bottom-up, i.e. verbs are first analyzed and then grouped into frames for each language separately. Specialized verbs are said to evoke a semantic frame, a sort of conceptual scenario in which a number of mandatory elements (core Frame Elements) play specific roles (e.g. ARGUER, JUDGE, LAW), but specialized verbs are often accompanied by other optional information (non-core Frame Elements), such as the criteria and reasons used by the judge to reach a decision (statutes, codes, previous decisions). The information concerning the semantic frame that each verb evokes was encoded in an xml editor and about twenty contexts illustrating the specific way each specialized verb evokes a given frame were semantically and syntactically annotated. The labels attributed to each semantic frame (e.g. [Compliance], [Verdict]) were used to group together certain synonyms, antonyms as well as equivalent terms. The research identified 165 pairs of candidate equivalents among the 200 Portuguese and English terms that were grouped together into 76 frames. 71% of the pairs of equivalents were considered full equivalents because not only do the verbs evoke the same conceptual scenario but their actantial structures, the linguistic realizations of the actants and their syntactic patterns were similar. 29% of the pairs of equivalents did not entirely meet these criteria and were considered partial equivalents. Reasons for partial equivalence are provided along with illustrative examples. Finally, the study describes the semasiological and onomasiological entry points that JuriDiCo, the bilingual lexical resource compiled during the project, offers to future users.

Représentation OWL de la ressource lexicale LVF et son utilisation dans le traitement automatique de la langue

Le dictionnaire LVF (Les Verbes Français) de J. Dubois et F. Dubois-Charlier représente une des ressources lexicales les plus importantes dans la langue française qui est caractérisée par une description sémantique et syntaxique très pertinente. Le LVF a été mis disponible sous un format XML pour rendre l’accès aux informations plus commode pour les applications informatiques telles que les applications de traitement automatique de la langue française. Avec l’émergence du web sémantique et la diffusion rapide de ses technologies et standards tels que XML, RDF/RDFS et OWL, il serait intéressant de représenter LVF en un langage plus formalisé afin de mieux l’exploiter par les applications du traitement automatique de la langue ou du web sémantique. Nous en présentons dans ce mémoire une version ontologique OWL en détaillant le processus de transformation de la version XML à OWL et nous en démontrons son utilisation dans le domaine du traitement automatique de la langue avec une application d’annotation sémantique développée dans GATE.

Text Comprehension And roduction in University Students: Text Reformulation

This paper sets out to report on findings about features of task-specific reformulation observed in university students in the middle stretch of the Psychology degree course (N=58) and in a reference group of students from the degree courses in Modern Languages, Spanish and Library Studies (N=33) from the National University of La Plata (Argentina). Three types of reformulation were modeled: summary reformulation, comprehensive and productive reformulation.The study was based on a corpus of 621 reformulations rendered from different kinds of text. The versions obtained were categorised according to the following criteria: presence or absence of normative, morphosyntactic and semantic difficulties. Findings show that problems arise particularly with paraphrase and summary writing. Observation showed difficulties concerning punctuation, text cohesion and coherence , and semantic distortion or omission as regards extracting and/or substituting gist, with limited lexical resources and confusion as to suitability of style/register in writing. The findings in this study match those of earlier, more comprehensive research on the issue and report on problems experienced by a significant number of university students when interacting with both academic texts and others of a general nature. Moreover, they led to questions, on the one hand, as to the nature of such difficulties, which appear to be production-related problems and indirectly account for inadequate text comprehension, and on the other hand, as to the features of university tuition when it comes to text handling.

Text Comprehension And roduction in University Students: Text Reformulation

This paper sets out to report on findings about features of task-specific reformulation observed in university students in the middle stretch of the Psychology degree course (N=58) and in a reference group of students from the degree courses in Modern Languages, Spanish and Library Studies (N=33) from the National University of La Plata (Argentina). Three types of reformulation were modeled: summary reformulation, comprehensive and productive reformulation.The study was based on a corpus of 621 reformulations rendered from different kinds of text. The versions obtained were categorised according to the following criteria: presence or absence of normative, morphosyntactic and semantic difficulties. Findings show that problems arise particularly with paraphrase and summary writing. Observation showed difficulties concerning punctuation, text cohesion and coherence , and semantic distortion or omission as regards extracting and/or substituting gist, with limited lexical resources and confusion as to suitability of style/register in writing. The findings in this study match those of earlier, more comprehensive research on the issue and report on problems experienced by a significant number of university students when interacting with both academic texts and others of a general nature. Moreover, they led to questions, on the one hand, as to the nature of such difficulties, which appear to be production-related problems and indirectly account for inadequate text comprehension, and on the other hand, as to the features of university tuition when it comes to text handling.

Text Comprehension And roduction in University Students: Text Reformulation

This paper sets out to report on findings about features of task-specific reformulation observed in university students in the middle stretch of the Psychology degree course (N=58) and in a reference group of students from the degree courses in Modern Languages, Spanish and Library Studies (N=33) from the National University of La Plata (Argentina). Three types of reformulation were modeled: summary reformulation, comprehensive and productive reformulation.The study was based on a corpus of 621 reformulations rendered from different kinds of text. The versions obtained were categorised according to the following criteria: presence or absence of normative, morphosyntactic and semantic difficulties. Findings show that problems arise particularly with paraphrase and summary writing. Observation showed difficulties concerning punctuation, text cohesion and coherence , and semantic distortion or omission as regards extracting and/or substituting gist, with limited lexical resources and confusion as to suitability of style/register in writing. The findings in this study match those of earlier, more comprehensive research on the issue and report on problems experienced by a significant number of university students when interacting with both academic texts and others of a general nature. Moreover, they led to questions, on the one hand, as to the nature of such difficulties, which appear to be production-related problems and indirectly account for inadequate text comprehension, and on the other hand, as to the features of university tuition when it comes to text handling.

Onyx: A Linked Data approach to emotion representation

Extracting opinions and emotions from text is becoming increasingly important, especially since the advent of micro-blogging and social networking. Opinion mining is particularly popular and now gathers many public services, datasets and lexical resources. Unfortunately, there are few available lexical and semantic resources for emotion recognition that could foster the development of new emotion aware services and applications. The diversity of theories of emotion and the absence of a common vocabulary are two of the main barriers to the development of such resources. This situation motivated the creation of Onyx, a semantic vocabulary of emotions with a focus on lexical resources and emotion analysis services. It follows a linguistic Linked Data approach, it is aligned with the Provenance Ontology, and it has been integrated with the Lexicon Model for Ontologies (lemon), a popular RDF model for representing lexical entries. This approach also means a new and interesting way to work with different theories of emotion. As part of this work, Onyx has been aligned with EmotionML and WordNet-Affect.