Online user comments contain valuable user opinions. Comments vary greatly in quality and detecting high quality comments is a subtask of opinion mining and summarization research. Finding attentive comments that provide some reasoning is highly valuable in understanding the user’s opinion particularly in sociopolitical opinion mining and aids policy makers, social organizations or government s...

This chapter introduces a method re-using a thesaurus built for a given domain, in order to create new resources of a higher semantic level in the form of an ontology. Considering ontologies for data-mining tasks relies on the intuition that the meaning of textual information depends on the conceptual relations between the objects to which they refer rather than on the linguistic and statistica...

Discovering relations among Named Entities (NEs) from large corpora is both a challenging, as well as useful task in the domain of Natural Language Processing, with applications in Information Retrieval (IR), Summarization (SUM), Question Answering (QA) and Textual Entailment (TE). The work we present resulted from the attempt to solve practical issues we were confronted with while building sys...

This paper addresses question analysis in the framework of Question Answering over structured data. The problem is set as a relation extraction task, where all the relations of interest in a given domain have to be extracted from natural language questions. The proposed approach applies the notion of Textual Entailment to compare the input questions with a repository of relational textual patte...

Nowadays we are facing a growing demand for semantic knowledge in computational applications, particularly in Natural Language Processing (NLP). However, there aren’t sufficient human resources to produce that knowledge at the same rate of its demand. Considering the Portuguese language, which has few resources in the semantic area, the situation is even more alarming. Aiming to solve that prob...

In this paper we introduce Elucidative Programming as a variant of Literate Programming. Literate Programming represents the idea of organizing a source program in an essay that documents the program understanding. An elucidative program connects textual documentation with the abstractions and the details in the source program. The documentation and the source program are defined in separate fi...

We present DEFIE, an approach to largescale Information Extraction (IE) based on a syntactic-semantic analysis of textual definitions. Given a large corpus of definitions we leverage syntactic dependencies to reduce data sparsity, then disambiguate the arguments and content words of the relation strings, and finally exploit the resulting information to organize the acquired relations hierarchic...

This document outlines our protocol for labeling noun pairs according to the entailment relations proposed by Bill MacCartney in his 2009 thesis on Natural Language Inference. Our purpose of doing this is to build a labelled data set with which to train a classifier for differentiating between these relations. The classifier can be used to assign probabilities of each relation to the paraphrase...

Discourse relations in the recent literature are typically classified as either explicit (e.g., when a discourse connective like “because” is present) or implicit. This binary treatment of implicitness is advantageous for simplifying the explanation of many phenomena in discourse processing. On the other hand, linguists do not yet agree as to what types of textual particles contribute to reveal...