Subtree Mining for Relation Extraction from Wikipedia
نویسندگان
چکیده
In this study, we address the problem of extracting relations between entities fromWikipedia’s English articles. Our proposed method first anchors the appearance of entities in Wikipedia’s articles using neither Named Entity Recognizer (NER) nor coreference resolution tool. It then classifies the relationships between entity pairs using SVM with features extracted from the web structure and subtrees mined from the syntactic structure of text. We evaluate our method on manually annotated data from actual Wikipedia articles.
منابع مشابه
Relation Extraction from Wikipedia Using Subtree Mining
The exponential growth and reliability of Wikipedia have made it a promising data source for intelligent systems. The first challenge of Wikipedia is to make the encyclopedia machine-processable. In this study, we address the problem of extracting relations among entities from Wikipedia’s English articles, which in turn can serve for intelligent systems to satisfy users’ information needs. Our ...
متن کاملWikipedia Link Structure and Text Mining for Semantic Relation Extraction
Wikipedia, a collaborative Wiki-based encyclopedia, has become a huge phenomenon among Internet users. It covers huge number of concepts of various fields such as Arts, Geography, History, Science, Sports and Games. Since it is becoming a database storing all human knowledge, Wikipedia mining is a promising approach that bridges the Semantic Web and the Social Web (a. k. a. Web 2.0). In fact, i...
متن کاملAn Integrated Approach for Relation Extraction from Wikipedia Texts
Linguistic-based methods and web mining-based methods are two types of leading methods for semantic relation extraction task. By integrating linguistic analysis with frequent Web information, this paper presents an unsupervised relation extraction approach, for discovering and enhancing relations in which a specified concept participates. We focus on concepts described in Wikipedia articles. By...
متن کاملTaxonomic Relation Extraction from Wikipedia: Datasets and Algorithms
The dynamic and continuously growing category structure of Wikipedia has been used in numerous ontology extraction methods. We present a dataset of category subgraphs automatically extracted from Wikipedia that are manually annotated for is-a and instance-of relations in order to enable a more comprehensive evaluation of taxonomy mining approaches. We also show how the new dataset can be used w...
متن کاملUnsupervised Relation Extraction by Mining Wikipedia Texts Using Information from the Web
This paper presents an unsupervised relation extraction method for discovering and enhancing relations in which a specified concept in Wikipedia participates. Using respective characteristics of Wikipedia articles and Web corpus, we develop a clustering approach based on combinations of patterns: dependency patterns from dependency analysis of texts in Wikipedia, and surface patterns generated ...
متن کامل