A Corpus-Based Investigation of Definite Description Use

We present the results of a study of definite descriptions use in written texts aimed at assessing the feasibility of annotating corpora with information about definite description interpretation. We ran two experiments, in which subjects were asked to classify the uses of definite descriptions in a corpus of 33 newspaper articles, containing a total of 1412 definite descriptions. We measured the agreement among annotators about the classes assigned to definite descriptions, as well as the agreement about the antecedent assigned to those definites that the annotators classified as being related to an antecedent in the text. The most interesting result of this study from a corpus annotation perspective was the rather low agreement (K=0.63) that we obtained using versions of Hawkins' and Prince's classification schemes; better results (K=0.76) were obtained using the simplified scheme proposed by Fraurud that includes only two classes, first-mention and subsequent-mention. The agreement about antecedents was also not complete. These findings raise questions concerning the strategy of evaluating systems for definite description interpretation by comparing their results with a standardized annotation. From a linguistic point of view, the most interesting observations were the great number of discourse-new definites in our corpus (in one of our experiments, about 50% of the definites in the collection were classified as discourse-new, 30% as anaphoric, and 18% as associative/bridging) and the presence of definites which did not seem to require a complete disambiguation.Comment: 47 pages, uses fullname.sty and palatino.st

O enigma da Igreja de Santa Maria-a-Velha da Batalha

A história desta pequena igreja no fundo é igual a história de tantos outros monumentos do passado. Foi ela uma construção funcional, desejada e prestigiante, mas que perdeu importância de forma progressiva e até foi um obstáculo à modernização; caindo no esquecimento e sucessiva destruição. Da velha igreja poucos são os vestígios. Apenas uma lápide implantada num espaço vazio, que outrora lhe pertencia, com o intuito de perpetuar a sua memória

Belief Update in AgentSpeak-DL

In previous work (Moreira et al, DALT 2005) we proposed an extension for the belief base of AgentSpeak agents based on Description Logic (DL), aiming at enabling agent oriented programming to cope with recently proposed technologies for the Semantic Web. In such an extension an agent belief base contains the definition of complex concepts, besides specific factual knowledge. The foreseen advantages are: (i) more expressive queries to the belief base; (ii) a refined notion of belief update, which considers consistency of a belief addition; (iii) flexibility in plan searching allowed by subsumption relation between concepts; and (iv) knowledge sharing in a semantic web context (based on OWL). Following this proposal an extension of the well know Agent Speak interpreter, Jason, was presented by K lapiscak and Bordini in DALT 2008. Among the interesting open issues is how to deal with the addition of beliefs which violates ontology consistency. In this work discuss this problem related to ABox updating in the context of AgentSpeak-DL

Learning discourse-new references in portuguese texts

This work presents the evaluation of a discourse status classifier for the Portuguese language. It considers two distinguished classes of discourse novelty: Brand-new and New references. An evaluation of the relevant features according to different linguistic levels are presented in detail.IFIP International Conference on Artificial Intelligence in Theory and Practice - Speech and Natural LanguageRed de Universidades con Carreras en Informática (RedUNCI

Towards semantic alignment of heterogeneous structures and its application to digital humanities

Different variants of the notion of ‘alignment’ have been adopted in a range of areas, focusing on homogeneous structures (e.g., text alignment [8], database alignment [1] or ontology alignment [4]) or heterogeneous structures (e.g., annotation of text with on- tologies [3], alignment of dictionaries and ontologies [2], alignments between relational databases and ontologies [9]). These alignment approaches, however, take little account of the alignment of multiple structures. This type of approach is becoming increasingly necessary to manage the growing volume of unstructured information sources available on the Web (encyclopedias such as Wikipedia, social media data, etc.) and LOD knowl- edge bases. In addition, the approaches are mostly developed for the English language. These needs have to be addressed through a global vision of alignment that takes into account a multiplicity of structures in which knowledge can be expressed. This paper seeks a holistic approach to semantic computing and alignment, when considering het- erogeneous structures in which knowledge is represented.FCT CEECIND/01997/2017, UIDB/00057/202

An Argumentation Framework based on Confidence Degrees to Combine Ontology Mapping Approaches

Ontology mapping has a key importance for applications such as information retrieval, database integration, and agent-communication. This paper presents an Argumentation Framework, with confidence degrees associated to the arguments, to combine ontology mapping approaches. Our agents apply individual mapping algorithms and cooperate in order to exchange their local results (arguments). 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. The model is evaluated using a benchmark for ontology mapping. The results are promising especially what concerns precision

An extended value-based argumentation framework for ontology mapping with confidence degrees

Heuristics to combine different approaches for ontology mapping have been proposed in the literature. This paper proposes to use abstract argumentation frameworks to combine such approaches. We extend the Value-based Argumentation Framework (VAF)[2], in order to represent arguments with confidence degrees. Our agents apply individual mapping algorithms and cooperate in order to exchange their local results (arguments). Next, 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

An Argumentation Framework based on strength for Ontology Mapping

In the field of ontology mapping, using argumentation to combine different mapping approaches is an innovative research area. We had extended the Value-based Argumentation Framework (VAF) in order to represent arguments with confidence degrees, according to the similarity degree between the terms being mapped. The mappings are computed by agents using different mapping approaches. Based on their preferences and confidences, the agents compute their preferred mapping sets. The arguments in such preferred sets are viewed as the set of globally acceptable arguments. In previous work we had used discrete classes to represent the confidence degrees (certainty and uncertainty). In this paper, we propose to use continuous values from the interval [0,1]. Here, confidence is treated as strength. Using a threshold for the strength we can reduce the set of mappings and adjust the values of precision. We evaluate the use of strength against the previous confidence as discrete classes. The results are promising, especially what concerns precision

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