Ontology Mapping for a Legal Question Answering System

Legal information retrieval systems, such question answering, use legal ontologies to represent semantic objects, to associate them with legal documents and to make inferences about them. The ontology mapping process can help users to reuse and compare information from different ontologies. In this paper we present a review on legal ontologies and present an approach to ontology mapping based on argumentation. Individual mappings are computed by specialized agents using different mapping approaches. Next, these agents use argumentation to exchange their local results, in order to agree on the obtained mappings. To each argument is associated a strength, representing how confident an agent is in the similarity of two ontology terms. Based on their preferences and confidence of the arguments, the agents compute their preferred mapping sets. The arguments in such preferred sets are viewed as the set of globally acceptable arguments. This work is part of a question answering system for the legal domain

KYOTO: A System for Mining, Structuring, and Distributing Knowledge Across Languages and Cultures

We outline work performed within the framework of a current EC project. The goal is to construct a language-independent information system for a specific domain (environment/ecology/biodiversity) anchored in a language-independent ontology that is linked to wordnets in seven languages. For each language, information extraction and identification of lexicalized concepts with ontological entries is carried out by text miners (?Kybots?). The mapping of language-specific lexemes to the ontology allows for crosslinguistic identification and translation of equivalent terms. The infrastructure developed within this project enables long-range knowledge sharing and transfer across many languages and cultures, addressing the need for global and uniform transition of knowledge beyond the specific domains addressed here

Senso Comune as a Knowledge Base of Italian language: The Resource and its Development

International audienceSenso Comune is a linguistic knowledge base for the Italian Language, which accommodates the content of a legacy dictionary in a rich formal model. The model is implemented in a platform which allows a community of contributors to enrich the resource. We provide here an overview of the main project features, including the lexical-ontology model, the process of sense classification, and the annotation of meaning definitions (glosses) and lexicographic examples. Also, we will illustrate the latest work of alignment with MultiWordNet, to illustrate the methodologies that have been experimented with, to share some preliminary result, and to highlight some remarkable findings about the semantic coverage of the two resources

Lexically-based Ontologies and Ontologically Based Lexicons

This paper deals with the relations between ontologies and lexicons. We study the role of these two components and their evolution during the last years in the field of Computational Linguistics. Subsequently, we survey the current lines of research at ILC-CNR which tackle this topic. They involve (I) the reuse of already existing Lexical Resources to derive formal ontologies, (II) the conversion and combination of terminologies into rich and formal Lexical Resources and (III) the use of formal ontologies as the backbone of multilingual Lexical Resources

Matching Law Ontologies using an Extended Argumentation Framework based on Confidence Degrees

Law information retrieval systems use law ontologies to represent semantic objects, to associate them with law documents and to make inferences about them. A number of law ontologies have been proposed in the literature, what shows the variety of approaches pointing to the need of matching systems. We present a proposal based on argumentation to match law ontologies, as an approach to be considered for this problem. Argumentation is used to combine different techniques for ontology matching. Such approaches are encapsulated by agents that apply individual matching algorithms and cooperate in order to exchange their local results (arguments). Next, based on their preferences and confidence, the agents compute their preferred matching sets. The arguments in such preferred sets are viewed as the set of globally acceptable arguments. We show the applicability of our model matching two legal core ontologies: LKIF and CLO

Ontological Engineering: What are Ontologies and How Can We Build Them?

Ontologies are formal, explicit specifications of shared conceptualizations. There is much literature on what they are, how they can be engineered and where they can be used inside applications. All these literature can be grouped under the term “Ontological Engineering,” which is defined as the set of activities that concern the ontology development process, the ontology lifecycle, the principles, methods and methodologies for building ontologies, and the tool suites and languages that support them. In this chapter we provide an overview of Ontological Engineering, describing the current trends, issues and problem

Knowledge-based methods for automatic extraction of domain-specific ontologies

Semantic web technology aims at developing methodologies for representing large amount of knowledge in web accessible form. The semantics of knowledge should be easy to interpret and understand by computer programs, so that sharing and utilizing knowledge across the Web would be possible. Domain specific ontologies form the basis for knowledge representation in the semantic web. Research on automated development of ontologies from texts has become increasingly important because manual construction of ontologies is labor intensive and costly, and, at the same time, large amount of texts for individual domains is already available in electronic form. However, automatic extraction of domain specific ontologies is challenging due to the unstructured nature of texts and inherent semantic ambiguities in natural language. Moreover, the large size of texts to be processed renders full-fledged natural language processing methods infeasible. In this dissertation, we develop a set of knowledge-based techniques for automatic extraction of ontological components (concepts, taxonomic and non-taxonomic relations) from domain texts. The proposed methods combine information retrieval metrics, lexical knowledge-base(like WordNet), machine learning techniques, heuristics, and statistical approaches to meet the challenge of the task. These methods are domain-independent and automatic approaches. For extraction of concepts, the proposed WNSCA+{PE, POP} method utilizes the lexical knowledge base WordNet to improve precision and recall over the traditional information retrieval metrics. A WordNet-based approach, the compound term heuristic, and a supervised learning approach are developed for taxonomy extraction. We also developed a weighted word-sense disambiguation method for use with the WordNet-based approach. An unsupervised approach using log-likelihood ratios is proposed for extracting non-taxonomic relations. Further more, a supervised approach is investigated to learn the semantic constraints for identifying relations from prepositional phrases. The proposed methods are validated by experiments with the Electronic Voting and the Tender Offers, Mergers, and Acquisitions domain corpus. Experimental results and comparisons with some existing approaches clearly indicate the superiority of our methods. In summary, a good combination of information retrieval, lexical knowledge base, statistics and machine learning methods in this study has led to the techniques efficient and effective for extracting ontological components automatically

The Lexical Grid: Lexical Resources in Language Infrastructures

Language Resources are recognized as a central and strategic for the development of any Human Language Technology system and application product. they play a critical role as horizontal technology and have been recognized in many occasions as a priority also by national and spra-national funding a number of initiatives (such as EAGLES, ISLE, ELRA) to establish some sort of coordination of LR activities, and a number of large LR creation projects, both in the written and in the speech areas