A Study of Polysemy and Sense Proximity in the Senseval-2 Test Suite
نویسندگان
چکیده
We report on an empirical study of sense relations in the Senseval-2 test suite. We apply and extend the method described in (Resnik and Yarowsky, 1999), estimating proximity of sense pairs from the evidence collected from native-speaker translations of 508 contexts across 4 Indoeuropean languages representing 3 language families. A control set composed of 65 contexts has also been annotated in 12 languages (including 2 non-Indoeuropean languages) in order to estimate the correlation between parallel polysemy and language family distance. A new parameter, sense stability, is introduced to assess the homogeneity of each individual sense definition. Finally, we combine the sense proximity estimation with a classification of semantic relations between senses.
منابع مشابه
Automatic Association Of Web Directories With Word Senses
We describe an algorithm that combines lexical information (from WordNet 1.7) with Web directories (from the Open Directory Project) to associate word senses with such directories. Such associations can be used as rich characterizations to acquire sense-tagged corpora automatically, cluster topically related senses, and detect sense specializations. The algorithm is evaluated for the 29 nouns (...
متن کاملAutomatic Association of Web Directories to Word Senses
We describe an algorithm that combines lexical information (from WordNet 1.7) with Web directories (from the Open Directory Project) to associate word senses with such directories. Such associations can be used as rich characterizations to acquire sense-tagged corpora automatically, cluster topically-related senses and detect sense specializations. The algorithm is evaluated for the 29 nouns (1...
متن کاملEvaluating the results of a memory-based word-expert approach to unrestricted word sense disambiguation
In this paper, we evaluate the results of the Antwerp University word sense disambiguation system in the English all words task of SENSEVAL-2. In this approach, specialized memory-based wordexperts were trained per word-POS combination. Through optimization by crossvalidation of the individual component classifiers and the voting scheme for combining them, the best possible word-expert was dete...
متن کاملWord Sense Disambiguation Using Vectors of Co-occurrence Information
This paper reports on the word sense disambiguation of Korean noun by using co-occurrence information in context. For a given noun, its local contextual word distribution is not enough to express their semantic characteristics for noun sense disambiguation. This paper proposes a cluster-based sense as a base vector. Contextual noise is removed by a term weighting method, and hypernyms of remain...
متن کاملAn Empirical Evaluation of Knowledge Sources and Learning Algorithms for Word Sense Disambiguation
In this paper, we evaluate a variety of knowledge sources and supervised learning algorithms for word sense disambiguation on SENSEVAL-2 and SENSEVAL-1 data. Our knowledge sources include the part-of-speech of neighboring words, single words in the surrounding context, local collocations, and syntactic relations. The learning algorithms evaluated include Support Vector Machines (SVM), Naive Bay...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2002