Addressing Ambiguity in Unsupervised Part-of-Speech Induction with Substitute Vectors
نویسنده
چکیده
We study substitute vectors to solve the part-of-speech ambiguity problem in an unsupervised setting. Part-of-speech tagging is a crucial preliminary process in many natural language processing applications. Because many words in natural languages have more than one part-of-speech tag, resolving part-of-speech ambiguity is an important task. We claim that partof-speech ambiguity can be solved using substitute vectors. A substitute vector is constructed with possible substitutes of a target word. This study is built on previous work which has proven that word substitutes are very fruitful for part-ofspeech induction. Experiments show that our methodology works for words with high ambiguity.
منابع مشابه
Word Context and Token Representations from Paradigmatic Relations and Their Application to Part-of-Speech Induction
Representation of words as dense real vectors in the Euclidean space provides an intuitive definition of relatedness in terms of the distance or the angle between one another. Regions occupied by these word representations reveal syntactic and semantic traits of the words. On top of that, word representations can be incorporated in other natural language processing algorithms as features. In th...
متن کاملPart of Speech Induction using Non-negative Matrix Factorization
Unsupervised part-of-speech induction involves the discovery of syntactic categories in a text, given no additional information other than the text itself. One requirement of an induction system is the ability to handle multiple categories for each word, in order to deal with word sense ambiguity. We construct an algorithm for unsupervised part-of-speech induction, treating the problem as one o...
متن کاملUsing DEDICOM for Completely Unsupervised Part-of-Speech Tagging
A standard and widespread approach to part-of-speech tagging is based on Hidden Markov Models (HMMs). An alternative approach, pioneered by Schütze (1993), induces parts of speech from scratch using singular value decomposition (SVD). We introduce DEDICOM as an alternative to SVD for part-of-speech induction. DEDICOM retains the advantages of SVD in that it is completely unsupervised: no prior ...
متن کاملEvaluating Unsupervised Part-of-Speech Tagging for Grammar Induction
This paper explores the relationship between various measures of unsupervised part-of-speech tag induction and the performance of both supervised and unsupervised parsing models trained on induced tags. We find that no standard tagging metrics correlate well with unsupervised parsing performance, and several metrics grounded in information theory have no strong relationship with even supervised...
متن کاملAn Improved Approach for Word Ambiguity Removal
Word ambiguity removal is a task of removing ambiguity from a word, i.e. correct sense of word is identified from ambiguous sentences. This paper describes a model that uses Part of Speech tagger and three categories for word sense disambiguation (WSD). Human Computer Interaction is very needful to improve interactions between users and computers. For this, the Supervised and Unsupervised metho...
متن کامل