The work we present here is concerned with the acquisition of deep grammatical information for nouns in Spanish. The aim is to build a learner that can handle noise, but, more interestingly, that is able to overcome the ...

Automatic creation of polarity lexicons is a crucial issue to be solved in order to reduce time and/nefforts in the first steps of Sentiment Analysis. In this paper we present a methodology based on/nlinguistic cues that ...

We present the results of the experiment of bootstrapping a Treebank for Catalan by using a Dependency Parser trained with Spanish sentences. In order to save time and cost, our approach was to profit from the typological ...

The aim of this study is to assess whether a brief training with rhythmic beat gestures helps L2 pronunciation in a reading aloud task with high school students. In a between-subjects pretest-posttest design, a total of ...

We study whether automatically-induced prompts that effectively extract information from a language model can also be used, out-of-the-box, to probe other language models for the same information. After confirming that ...

Linking implicit semantic roles is a challenging problem in discourse processing. Unlike prior work inspired by SRL, we cast this problem as an anaphora resolution task and embed it in an entity-based coreference ...

To successfully account for language, computational models need to take into account both the linguistic context (the content of the utterances) and the extra-linguistic context (for instance, the participants in a dialogue). ...

This paper describes an effort to capture the sense alternation of dot-type nominals using Word Sense Induction (WSI). We propose dot-type nominals generate more semantically consistent groupings when clustered into more ...

The vast majority of Machine Translation (MT) evaluation approaches are based on the idea that the closer the MT output is to a human reference translation, the higher its quality. While translation quality has two ...

The present work investigates whether different quantification mechanisms (set comparison, vague quantification, and proportional estimation) can be jointly learned from visual scenes by a multi-task computational model. ...