We study the impact of syntactic and shallow semantic information in automatic classification of questions and answers and answer re-ranking. We define (a) new tree structures based on shallow semantics encoded in Predicate Argument Structures (PASs) and (b) new kernel functions to exploit the representational power of such structures with Support Vector Machines. Our experiments suggest that s...

In this paper we explore how compositional semantics, discourse structure, and the cogni-tive states of participants all contribute to pragmatic constraints on answers to questions in dialogue. We synthesise formal semantic theories on questions and answers with techniques for discourse interpretation familiar from computational linguistics, and show how this provides richer constraints on resp...

In recent algebra investigations, the maximum number of islands on some grid turned out to appear as interesting combinatorial problem. The aim of this paper is to overview the history and the results in this topic. The first result, the formula of Gábor Czédli appeared in [2], his proof was based on lattice theory. The investigation went on two different directions, nowadays both are living re...

Open forum threads exhibit a great variability in the quality and quantity of the answers they attract, making it difficult to manually moderate and separate relevant from irrelevant content. The goal of SemEval 2015 Task 3 (Subtask A, English) is to build systems that automatically distinguish between relevant and irrelevant content in forum threads. We extend a short answer assessment system ...

This paper describes the KeLP system participating in the SemEval-2016 Community Question Answering (cQA) task. The challenge tasks are modeled as binary classification problems: kernel-based classifiers are trained on the SemEval datasets and their scores are used to sort the instances and produce the final ranking. All classifiers and kernels have been implemented within the Kernel-based Lear...

This paper describes the Entrance Exams task at the CLEF QA Track 2015. Following the last two editions, the data set has been extracted from actual university entrance examinations including a variety of topics and question types. Systems receive a set of Multiple-Choice Reading Comprehension tests where the task is to select the correct answer among a finite set of candidates, according to th...

We present a Question Answering system for technical domains which makes an intelligent use of paraphrases to increase the likelihood of finding the answer to the user’s question. The system implements a simple and efficient logic representation of questions and answers that maps paraphrases to the same underlying semantic representation. Further, paraphrases of technical terminology are dealt ...

In this paper, we explore the utility of attitude types for improving question answering (QA) on both web-based discussions and news data. We present a set of attitude types developed with an eye toward QA and show that they can be reliably annotated. Using the attitude annotations, we develop automatic classifiers for recognizing two main types of attitudes: sentiment and arguing. Finally, we ...

We present the implementation of an autonomous chatbot, SHIHbot, deployed on Facebook, which answers a wide variety of sexual health questions on HIV/AIDS. The chatbot's response database is compiled from professional medical and public health resources in order to provide reliable information to users. The system's backend is NPCEditor, a response selection platform trained on linked questions...