Augmenting WordNet-like lexical resources with distributional evidence. An application-oriented perspective
نویسندگان
چکیده
The paper deals with the issue of how and to what extent WordNet-like resources provide the necessary information for an assessment of semantic similarity which is useful for practical applications. The general point is made that taxonomical information should be complemented with distributional evidence. The claim is substantiated through experimental data and an illustration of a word sense disambiguation system (SENSE) capable of using contextually-relevant semantic similarity.
منابع مشابه
Towards Improving Synonym Options in a Text Modification Application
The Language Musesystem (LM) is an application that supports classroom teachers in text modification for middleand highschool learners who are non-native English speakers (NNES). The application performs linguistic analysis on classroom texts highlighting lexical, syntactic, and pragmatic features, indicating potential areas of linguistic complexity. One of the lexical feature options that LM o...
متن کاملAugmenting Approximate Similarity Searching with Lexical Information
Accurately representing synonymy using distributional similarity requires large volumes of data to reliably represent infrequent words. However, the naı̈ve nearest-neighbour approach to compare context vectors extracted from large corpora scales poorly. The Spatial Approximation Sample Hierarchy (SASH) is a data-structure for performing approximate nearest-neighbour queries, and has been previou...
متن کاملBabelDomains: Large-Scale Domain Labeling of Lexical Resources
In this paper we present BabelDomains, a unified resource which provides lexical items with information about domains of knowledge. We propose an automatic method that uses knowledge from various lexical resources, exploiting both distributional and graph-based clues, to accurately propagate domain information. We evaluate our methodology intrinsically on two lexical resources (WordNet and Babe...
متن کاملIdentifying Lexical Relationships and Entailments with Distributional Semantics
As the field of Natural Language Processing has developed, research has progressed on ambitious semantic tasks like Recognizing Textual Entailment (RTE). Systems that approach these tasks may perform sophisticated inference between sentences, but often depend heavily on lexical resources like WordNet to provide critical information about relationships and entailments between lexical items. Howe...
متن کاملSyntactic/Semantic Structures for Textual Entailment Recognition
In this paper, we describe an approach based on off-the-shelf parsers and semantic resources for the Recognizing Textual Entailment (RTE) challenge that can be generally applied to any domain. Syntax is exploited by means of tree kernels whereas lexical semantics is derived from heterogeneous resources, e.g. WordNet or distributional semantics through Wikipedia. The joint syntactic/semantic mod...
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 1998