Pattern-Based Disambiguation for Natural Language Processing
نویسنده
چکیده
A wide range of natural language problems can be viewed as disambiguating between a small set of alternatives based upon the string context surrounding the ambiguity site. In this paper we demonstrate that classification accuracy can be improved by invoking a more descriptive feature set than what is typically used. We present a technique that disambiguates by learning regular expressions describing the string contexts in which the ambiguity sites appear.
منابع مشابه
SePaS: Word sense disambiguation by sequential patterns in sentences
An open problem in natural language processing is word sense disambiguation (WSD). A word may have several meanings, but WSD is the task of selecting the correct sense of a polysemous word based on its context. Proposed solutions are based on supervised and unsupervised learning methods. The majority of researchers in the area focused on choosing proper size of ‘n’ in n-gram that is used for WS...
متن کاملKernel Fuzzy C-Means Clustering for Word Sense Disambiguation in
Word sense disambiguation (WSD) in biomedical texts is important. The majority of existing research primarily focuses on supervised learning methods and knowledge-based approaches. Implementing these methods requires significant human-annotated corpus, which is not easily obtained. In this paper, we developed an unsupervised system for WSD in biomedical texts. First, we predefine the number of ...
متن کاملDisambiguating Verbs by Collocation: Corpus Lexicography meets Natural Language Processing
This paper reports the results of Natural Language Processing (NLP) experiments in semantic parsing, based on a new semantic resource, the Pattern Dictionary of English Verbs (PDEV) (Hanks, 2013). This work is set in the DVC (Disambiguating Verbs by Collocation) project aimed at expanding PDEV to a large scale. This project springs from a long-term collaboration of lexicographers with computer ...
متن کاملNetworks and Natural Language Processing
Over the last few years, a number of areas of natural language processing have begun applying graph-based techniques. These include, among others, text summarization, syntactic parsing, word sense disambiguation, ontology construction, sentiment and subjectivity analysis, text clustering. In this paper, we present some of the most successful graph-based representations and algorithms used in la...
متن کاملGraph Based Algorithms for Word Sense Induction and Disambiguation
This paper presents a survey of graph based methods for word sense induction and disambiguation. Many areas of Natural Language Processing like Word Sense Disambiguation (WSD), text summarization, keyword extraction make use of Graph based methods. The very idea behind graph based approach is to formulate the problems in graph setting and apply clustering to obtain a set of clusters (senses). T...
متن کامل