Articles

AbstractWe present a study of the adequacy of current methods that are used for POS-tagging historical Dutch texts, as well as an exploration of the influence of employing different techniques to improve upon the current practice. The main focus of this paper is on (unsupervised) methods that are easily adaptable …...

AbstractWe address the task of automatically estimating the missing values of linguistic features by making use of the fact that some linguistic features in typological databases are informative to each other. The questions to address in this work are (i) how much predictive power do features have on the value …...

AbstractEmotion Recognition (ER) is an important part of dialogue analysis which can be used in order to improve the quality of Spoken Dialogue Systems (SDSs). The emotional hypothesis of the current response of an end-user might be utilised by the dialogue manager component in order to change the SDS strategy …...

AbstractIn this paper, we analyze the sentiments derived from the conversations that occur in social networks. Our goal is to identify the sentiments of the users in the social network through their conversations. We conduct a study to determine whether users of social networks (twitter in particular) tend to gather …...

AbstractA key point in Sentiment Analysis is to determine the polarity of the sentiment implied by a certain word or expression. In basic Sentiment Analysis systems this sentiment polarity of the words is accounted and weighted in different ways to provide a degree of positivity/negativity. Currently words are also modelled …...

AbstractSentiment Analysis systems aims at detecting opinions and sentiments that are expressed in texts. Many approaches in literature are based on resources that model the prior polarity of words or multi-word expressions, i.e. a polarity lexicon. Such resources are defined by teams of annotators, i.e. a manual annotation is provided …...

AbstractExisting Arabic sentiment lexicons have low coverage―with only a few thousand entries. In this paper, we present several large sentiment lexicons that were automatically generated using two different methods: (1) by using distant supervision techniques on Arabic tweets, and (2) by translating English sentiment lexicons into Arabic using a freely …...

AbstractWe present a freely available corpus containing source language texts from different domains along with their automatically generated translations into several distinct morphologically rich languages, their post-edited versions, and error annotations of the performed post-edit operations. We believe that the corpus will be useful for many different applications. The main …...

AbstractWhile an increasing number of (automatic) metrics is available to assess the linguistic quality of machine translations, their interpretation remains cryptic to many users, specifically in the translation community. They are clearly useful for indicating certain overarching trends, but say little about actual improvements for translation buyers or post-editors. However, …...

AbstractThe present work is an overview of the TraMOOC (Translation for Massive Open Online Courses) research and innovation project, a machine translation approach for online educational content. More specifically, videolectures, assignments, and MOOC forum text is automatically translated from English into eleven European and BRIC languages. Unlike previous approaches to …...

AbstractOut-of-vocabulary words (OOVs) are a ubiquitous and difficult problem in statistical machine translation (SMT). This paper studies different strategies of using BabelNet to alleviate the negative impact brought about by OOVs. BabelNet is a multilingual encyclopedic dictionary and a semantic network, which not only includes lexicographic and encyclopedic terms, but …...

AbstractIn this document we report on a user-scenario-based evaluation aiming at assessing the performance of machine translation (MT) systems in a real context of use. We describe a sequel of experiments that has been performed to estimate the usefulness of MT and to test if improvements of MT technology lead …...

This paper describes the participation of the TALN team in SemEval-2016 Task 14: Se- mantic Taxonomy Enrichment. The purpose of the task is to find the best point of attach- ment in WordNet for a set of Out of Vocabu- lary (OOV) terms. These may come, to name a few, …...

We present a system for taxonomy construc- tion that reached the first place in all sub- tasks of the SemEval 2016 challenge on Tax- onomy Extraction Evaluation. Our simple yet effective approach harvests hypernyms with substring inclusion and Hearst-style lexico- syntactic patterns from domain-specific texts obtained via language model based …...

This paper describes the Duluth systems that participated in Task 14 of SemEval 2016, Se- mantic Taxonomy Enrichment. There were three related systems in the formal evalua- tion which are discussed here, along with nu- merous post–evaluation runs. All of these systems identified synonyms between Word- Net and other dictionaries …...

This paper describes our approach to build a language-independent hypernym extrac- tion system, based on two modules for the SemEval-2016 Task 13 on Taxonomy Extrac- tion Evaluation (TExEval-2). This task fo- cuses only on the hypernym-hyponym rela- tion extraction from a list of terms collected from various domains and languages. …...

This paper describes our submission to the SemEval-2016 Taxonomy Extraction Evalua- tion (TExEval-2) Task. We examine the en- docentric nature of hyponyms and propose a simple rule-based method to identify hyper- nyms at high precision. For the food domain, we extract lists of terms from the Wikipedia lists of lists …...

This paper describes the NUIG-UNLP sys- tem submitted to SemEval-2016, Task 13. We implement a semi-supervised method that ex- tracts hypernym candidates for the terms pro- vided in the test list. The main assumption of our system is that hypernyms may be induced by adding a vector offset to the …...

This paper presents our participation to the Se- mEval “Task 13: Taxonomy Extraction Evalu- ation (TExEval-2)” (Bordea et al., 2016). This year, we propose the combination of recent se- mantic vectors representation into a method- ology for semisupervised and auto-supervised acquisition of lexical taxonomies from raw texts. In our proposal, …...

In this paper, we describe the system de- veloped for our participation in the Clinical TempEval task of SemEval 2016 (task 12). Our team focused on the subtasks of span and attribute identification from raw text and proposed a system that integrates both statis- tical and linguistic approaches. Our system …...