6 papers · 1 filter
A Comparison between Supervised Learning Algorithms for Word Sense Disambiguation
Gerard Escudero, Lluis Marquez, German Rigau
This paper describes a set of comparative experiments, including cross-corpus evaluation, between five alternative algorithms for supervised Word Sense Disambiguation (WSD), namely…
Mapping WordNets Using Structural Information
J. Daude, L. Padro, G. Rigau
We present a robust approach for linking already existing lexical/semantic hierarchies. We used a constraint satisfaction algorithm (relaxation labeling) to select --among a set of…
Naive Bayes and Exemplar-Based approaches to Word Sense Disambiguation Revisited
Gerard Escudero, Lluis Marquez, German Rigau
This paper describes an experimental comparison between two standard supervised learning methods, namely Naive Bayes and Exemplar-based classification, on the Word Sense Disambigua…
Boosting Applied to Word Sense Disambiguation
Gerard Escudero, Lluis Marquez, German Rigau
In this paper Schapire and Singer's AdaBoost.MH boosting algorithm is applied to the Word Sense Disambiguation (WSD) problem. Initial experiments on a set of 15 selected polysemous…
Semantic Parsing based on Verbal Subcategorization
Jordi Atserias, Irene Castellon, Montse Civit +1
The aim of this work is to explore new methodologies on Semantic Parsing for unrestricted texts. Our approach follows the current trends in Information Extraction (IE) and is based…
Using a Diathesis Model for Semantic Parsing
Jordi Atserias, Irene Castellon, Montse Civit +1
This paper presents a semantic parsing approach for unrestricted texts. Semantic parsing is one of the major bottlenecks of Natural Language Understanding (NLU) systems and usually…