Synonymy and granularity in the WordNet-like lexical data bases

In this paper we present a contribution to the transformation of PolNet, a Polish wordnet developed at the Adam Mickiewicz University in Pozna, into a Lexicon Grammar of Polish. The current step consists in including verb-noun collocations and relations linking the verbal synsets to noun synsets. We focus on the concept of synonymy for two kinds of predicative entities: verbs and verb-noun collocations and on synset granularity problems that emerged at this stage of the project. This work was sponsored by the Polish National Program for Humanities (grant 0022/FNiTP/H11/80/2011).In this paper we present a contribution to the transformation of PolNet, a Polish wordnet developed at the Adam Mickiewicz University in Pozna, into a Lexicon Grammar of Polish. The current step consists in including verb-noun collocations and relations linking the verbal synsets to noun synsets. We focus on the concept of synonymy for two kinds of predicative entities: verbs and verb-noun collocations and on synset granularity problems that emerged at this stage of the project. This work was sponsored by the Polish National Program for Humanities (grant 0022/FNiTP/H11/80/2011)

Design of a Controlled Language for Critical Infrastructures Protection

We describe a project for the construction of controlled language for critical infrastructures protection (CIP). This project originates from the need to coordinate and categorize the communications on CIP at the European level. These communications can be physically represented by official documents, reports on incidents, informal communications and plain e-mail. We explore the application of traditional library science tools for the construction of controlled languages in order to achieve our goal. Our starting point is an analogous work done during the sixties in the field of nuclear science known as the Euratom Thesaurus.JRC.G.6-Security technology assessmen

On Singles, Couples and Extended Families. Measuring Overlapping between Latin Vallex and Latin WordNet

Different lexical resources may pursue different views on lexical meaning. However, all of them deal with lexical items as common basic components, which are described according to criteria that may vary from one resource to another. In this paper, we present a method for measuring the degree of similarity between a valency-based lexical resource and a WordNet. This is motivated by both theoretical and practical reasons. As for the former, we wonder if there are lexical classes that "impose" themselves regardless of the fact that they are explicitly recorded as such in source lexical resources. As for the latter, our work wants to contribute to the research task dealing with merging lexical resources. In order to apply and evaluate our method, we propose a normalized coefficient of overlapping that measures the overlapping rate between a valency lexicon and a WordNet. In particular, in the context of the exploitation of the linguistic resources for ancient languages built over the last decade, we compute and evaluate the overlapping between a selection of homogeneous lexical subsets extracted from two lexical resources for Latin

An ontology for human-like interaction systems

This report proposes and describes the development of a Ph.D. Thesis aimed at building an ontological knowledge model supporting Human-Like Interaction systems. The main function of such knowledge model in a human-like interaction system is to unify the representation of each concept, relating it to the appropriate terms, as well as to other concepts with which it shares semantic relations. When developing human-like interactive systems, the inclusion of an ontological module can be valuable for both supporting interaction between participants and enabling accurate cooperation of the diverse components of such an interaction system. On one hand, during human communication, the relation between cognition and messages relies in formalization of concepts, linked to terms (or words) in a language that will enable its utterance (at the expressive layer). Moreover, each participant has a unique conceptualization (ontology), different from other individual’s. Through interaction, is the intersection of both part’s conceptualization what enables communication. Therefore, for human-like interaction is crucial to have a strong conceptualization, backed by a vast net of terms linked to its concepts, and the ability of mapping it with any interlocutor’s ontology to support denotation. On the other hand, the diverse knowledge models comprising a human-like interaction system (situation model, user model, dialogue model, etc.) and its interface components (natural language processor, voice recognizer, gesture processor, etc.) will be continuously exchanging information during their operation. It is also required for them to share a solid base of references to concepts, providing consistency, completeness and quality to their processing. Besides, humans usually handle a certain range of similar concepts they can use when building messages. The subject of similarity has been and continues to be widely studied in the fields and literature of computer science, psychology and sociolinguistics. Good similarity measures are necessary for several techniques from these fields such as information retrieval, clustering, data-mining, sense disambiguation, ontology translation and automatic schema matching. Furthermore, the ontological component should also be able to perform certain inferential processes, such as the calculation of semantic similarity between concepts. The principal benefit gained from this procedure is the ability to substitute one concept for another based on a calculation of the similarity of the two, given specific circumstances. From the human’s perspective, the procedure enables referring to a given concept in cases where the interlocutor either does not know the term(s) initially applied to refer that concept, or does not know the concept itself. In the first case, the use of synonyms can do, while in the second one it will be necessary to refer the concept from some other similar (semantically-related) concepts...Programa Oficial de Doctorado en Ciencia y Tecnología InformáticaSecretario: Inés María Galván León.- Secretario: José María Cavero Barca.- Vocal: Yolanda García Rui

Acquiring and Harnessing Verb Knowledge for Multilingual Natural Language Processing

Advances in representation learning have enabled natural language processing models to derive non-negligible linguistic information directly from text corpora in an unsupervised fashion. However, this signal is underused in downstream tasks, where they tend to fall back on superficial cues and heuristics to solve the problem at hand. Further progress relies on identifying and filling the gaps in linguistic knowledge captured in their parameters. The objective of this thesis is to address these challenges focusing on the issues of resource scarcity, interpretability, and lexical knowledge injection, with an emphasis on the category of verbs. To this end, I propose a novel paradigm for efficient acquisition of lexical knowledge leveraging native speakers’ intuitions about verb meaning to support development and downstream performance of NLP models across languages. First, I investigate the potential of acquiring semantic verb classes from non-experts through manual clustering. This subsequently informs the development of a two-phase semantic dataset creation methodology, which combines semantic clustering with fine-grained semantic similarity judgments collected through spatial arrangements of lexical stimuli. The method is tested on English and then applied to a typologically diverse sample of languages to produce the first large-scale multilingual verb dataset of this kind. I demonstrate its utility as a diagnostic tool by carrying out a comprehensive evaluation of state-of-the-art NLP models, probing representation quality across languages and domains of verb meaning, and shedding light on their deficiencies. Subsequently, I directly address these shortcomings by injecting lexical knowledge into large pretrained language models. I demonstrate that external manually curated information about verbs’ lexical properties can support data-driven models in tasks where accurate verb processing is key. Moreover, I examine the potential of extending these benefits from resource-rich to resource-poor languages through translation-based transfer. The results emphasise the usefulness of human-generated lexical knowledge in supporting NLP models and suggest that time-efficient construction of lexicons similar to those developed in this work, especially in under-resourced languages, can play an important role in boosting their linguistic capacity.ESRC Doctoral Fellowship [ES/J500033/1], ERC Consolidator Grant LEXICAL [648909

Recent Advances in Development of a Lexicon-Grammar of Polish: PolNet 3.0

International audienceIn this paper we present recent works contributing to transformation of the initial PolNet, a Polish wordnet developed at the Adam Mickiewicz University, into a Lexicon Grammar of Polish. We focus on granularity issues that occurred at the stage of including verb-noun collocations as well as information related to language registers