Using natural language patterns for the development of ontologies

The combination of certain linguistic units that recurrently appear in text genres has attracted the attention of many researchers in several domains, as they can provide valuable information about different types of relations. In this paper, the focus will be on some of these combinatory units, referred to as Lexico-Syntactic Patterns (LSPs) that provide information about conceptual relations. The aim of this research is to detect recurrent patterns that express some of the most common conceptual relations present in ontologies. The purpose of this paper is to present the different strategies we have followed to identify LSPs which correspond to some of the main ontological relations, as well as an excerpt of the repository of LSPs that is currently being built

When Phraseology and Ontologies Meet

In the field of Languages for Specific Purposes, phraseology plays a central role since its mastering is crucial for the different users that deal with specialized languages, from professionals of a domain to linguist experts (terminologists, translators, communication mediators, etc.). According to Aguado de Cea (2007), phraseology can be defined as: “the linguistic discipline that deals with the combination of words”, (…), or “the set of phraseological units or phrasemes” of a certain specialized language. In any case, phrasemes or lexical combinations are not only necessary for an adequate specialized communication, but they are also fundamental in the understanding of a certain domain of knowledge, together with terms and the concepts underlying terms

Approaches to ontology development by non ontology experts

Untrained users in the development of ontologies are challenged by the formal representation languages that underlie the most common ontology editing tools. To reduce that barrier, many efforts have gone in the creation of Controlled Languages (CL) translatable into ontology structures. However, CLs fall short of addressing a more profound problem: the selection of the most appropriate ontology modelling component for a certain modelling problem, regardless of the underlying representation paradigm. With the aim of approaching non ontology expert's difficulties in selecting the most appropriate modelling solution, we propose a Natural Language (NL) guided approach based on a repository of Lexico-Syntactic Patterns associated to consensual modelling solutions, i.e., Ontology Design Patterns. By relying on this repository, untrained users can formulate in NL what they want to model in the ontology, and obtain the corresponding design pattern for the modelling issue

Using Linguistic Patterns to Enhance Ontology Development

In this paper we describe how linguistic patterns can contribute to ontology development by enabling an easier reuse of some ontological resources. In particular, our research focuses on the reuse of ontology design patterns and ontology statements by relying on linguistic constructs at different stages of the reuse process. With this aim, we propose the employment of lexico-syntactic patterns with two objectives: 1) the reuse of ontology design patterns, and 2) the validation of ontology statements for their subsequent reuse in the ontology development. To illustrate the proposed approaches, we will present some examples of lexico-syntactic patterns and their employment in the reuse of ontology design patterns and in the validation of ontology statements

Natural Language-based Approach for Helping in the Reuse of Ontology Design Patterns

Experiments in the reuse of Ontology Design Patterns (ODPs) have revealed that users with different levels of expertise in ontology modelling face difficulties when reusing ODPs. With the aim of tackling this problem we propose a method and a tool for supporting a semi-automatic reuse of ODPs that takes as input formulations in natural language (NL) of the domain aspect to be modelled, and obtains as output a set of ODPs for solving the initial ontological needs. The correspondence between ODPs and NL formulations is done through Lexico-Syntactic Patterns, linguistic constructs that convey the semantic relations present in ODPs, and which constitute the main contribution of this paper. The main benefit of the proposed approach is the use of non-restricted NL formulations in various languages for obtaining ODPs. The use of full NL poses challenges in the disambiguation of linguistic expressions that we expect to solve with user interaction, among other strategies

Automatic Acquisition of Ranked Qualia Structures from the Web

Cimiano P, Wenderoth J. Automatic Acquisition of Ranked Qualia Structures from the Web. In: Carroll JA, van den Bosch A, Zaenen A, eds. ACL 2007, Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics. 2007: 888-895

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