tailieunhanh - Báo cáo khoa học: "Detecting Semantic Relations between Named Entities in Text Using Contextual Features"

This paper proposes a supervised learning method for detecting a semantic relation between a given pair of named entities, which may be located in different sentences. The method employs newly introduced contextual features based on centering theory as well as conventional syntactic and word-based features. These features are organized as a tree structure and are fed into a boosting-based classification algorithm. Experimental results show the proposed method outperformed prior methods, and increased precision and recall by and . . | Detecting Semantic Relations between Named Entities in Text Using Contextual Features Toru Hirano Yoshihiro Matsuo Genichiro Kikui NTT Cyber Space Laboratories NTT Corporation 1-1 Hikarinooka Yokosuka-Shi Kanagawa 239-0847 Japan @ Abstract This paper proposes a supervised learning method for detecting a semantic relation between a given pair of named entities which may be located in different sentences. The method employs newly introduced contextual features based on centering theory as well as conventional syntactic and word-based features. These features are organized as a tree structure and are fed into a boosting-based classification algorithm. Experimental results show the proposed method outperformed prior methods and increased precision and recall by and . 1 Introduction Statistical and machine learning NLP techniques are now so advanced that named entity NE taggers are in practical use. Researchers are now focusing on extracting semantic relations between NEs such as George Bush person is president relation of the United States location because they provide important information used in information retrieval question answering and summarization. We represent a semantic relation between two NEs with a tuple NE1 NE2 Relation Label . Our final goal is to extract tuples from a text. For example the tuple George Bush person the . location president Relation Label would be extracted from the sentence George Bush is the president of the . . There are two tasks in extracting tuples from text. One is detecting whether or not a given pair of NEs are semantically related relation detection and the other is determining the relation label relation characterization . In this paper we address the task of relation detection. So far various supervised learning approaches have been explored in this field Culotta and Sorensen 2004 Zelenko et al. 2003 . They 157 use two kinds of features syntactic ones .