Articles

Word Sense Disambiguation is the task dedi- cated to the problem of finding out the sense of a word in context, from all of its many pos- sible senses. Solving this problem requires to know the set of possible senses for a given word, which can be acquired from human …...

We propose a new method which enables the training of a kernelized structured output model. The struc- tured output learning can flexibly represent a problem, and thus is gaining popularity in natural language pro- cessing. Meanwhile the polynomial kernel method is effective in many natural language processing tasks, since it …...

We present a comparison between two systems for establishing syntactic and semantic depen- dencies: one that performs dependency parsing and semantic role labeling as a single task, and another that performs the two tasks in isola- tion. The systems are based on local memory- based classifiers predicting syntactic and seman- …...

We present a compositional framework for modelling entity-level sentiment (sub)contexts, and demonstrate how holistic multi-entity polar- ity scoring emerges as a by-product of composi- tional sentiment parsing. A data set of five anno- tators’ multi-entity judgements is presented, and a human ceiling is established for the challenging new task. The …...

In this paper, we introduce the L´exico de Formas Flexionadas del Espa˜nol (Leffe), a wide-coverage morphological and syntactic Spanish lexicon based on the Alexina lexical framework. We explain how the Leffe has been created by merging together several heterogeneous lexicons and how the Alexina lexical framework has been applied to …...

For Arabic, diacritizing written text is impor- tant for many NLP tasks. In the work presented here, we investigate the quality of a diacritization approach, with a high success rate for treebank data but with a more limited success on real- world data. One of the problems we encountered is …...

This paper presents a new study on automatic terminology extraction in the context of bimodal corpora that were generated from lectures and meetings. More specifically, the study aims to observe to which extent written text (dis- cussed documents) and spoken text (dialogue transcript) share keywords. Using a hybrid ter- minology …...

In contrast with other NLP tasks, only few and limited evaluation challenges have been carried out for terminology acquisition. It is nevertheless important to assess the progress made, the qual- ity and limitations of terminological tools. This paper argues that it is possible to define evalua- tion protocols for tasks …...

In this paper an exploratory map of what intelligent natural language processing systems can achieve will be drawn up, given the advances that have been made in recent years as revealed in the latest developments in practical applications of natural language technology in areas as diverse as natural language generation, …...

Good hypertext writing style mandates that link texts clearly indicate the nature of the link tar- get. While this guideline is routinely ignored in HTML, the lightweight markup languages used by wikis encourage or even force hypertext au- thors to use semantically appropriate link texts. This property of wiki hypertext …...

The paper presents the results of a project com- pleted by the authors for realizing a contin- uous speech recognition system for Bulgarian. The state-of-the-art speech recognition technol- ogy used in the system is discussed. Special attention is given to the problems with some speci cs of the Bulgarian language …...

This paper presents a novel automatic approach to partially integrate FrameNet and WordNet. In that way we expect to extend FrameNet coverage, to en- rich WordNet with frame semantic information and possibly to extend FrameNet to languages other than English. The method uses a knowledge-based Word Sense Disambiguation algorithm for …...

The paper presents Treelex, a valence lexicon of French adjectives automatically extracted from a treebank. The corpus contains morphological and syntactic annotations but no subcategorisa- tion information is present for adjectives. Due to rich corpus annotations, our extraction method is guided by linguistic knowledge. The obtained lexicon (about 2000 adjectives …...

In this paper, we discuss the importance of the quality against the quantity of automatically ex- tracted examples for word sense disambiguation (WSD). We first show that we can build a com- petitive WSD system with a memory-based clas- sifier and a feature set reduced to easily and efficiently computable …...

In this paper, we present a novel, cognitively mo- tivated framework for modelling the cross-modal influence of visual scene context upon language processing. We illustrate how semantic relations in a knowledge representation of visual scene context can effect syntactic attachment modulations in a weighted- constraint dependency parser. In line with …...

We present a pilot experiment to measure the effects of redundancy in the resolution of definite descriptions as performed by a small number of human readers. Although originally intended to provide evidence of how much redundancy should ideally be included in generated anaphoric descriptions, preliminary findings reveal a number of …...

Conditional Random Fields are commonly trained to maximize likelihood. The corresponding Fβ measure, the weighted harmonic mean of preci- sion and recall, which is established for evaluation in information retrieval and text mining, is not necessarily the optimal result for the user’s choice of β. Some approaches have been published …...

Nowadays, the temporal aspects of natural lan- guage are receiving a great research interest. TimeML has been adopted as a standard for tem- poral information annotation by a large number of researchers. Available TimeML resources are very limited in size and in diversity of languages. This paper analyzes a combination …...

In the application of Conditional Random Fields (CRF), a huge number of features is typically taken into ac- count. These models can deal with inter-dependent and correlated data with an enormous complexity. The application of feature subset selection is important to improve performance, speed and explainability. We present and compare …...

We describe a pattern-based system for polarity classification from texts. Our system is currently restricted to the positive, negative or neutral po- larity of phrases and sentences. It analyses the input texts with the aid of a polarity lexicon that specifies the prior polarity of words. A chunker is used …...