Đang chuẩn bị liên kết để tải về tài liệu:
Báo cáo khoa học: "Word Sense and Subjectivity"

Subjectivity and meaning are both important properties of language. This paper explores their interaction, and brings empirical evidence in support of the hypotheses that (1) subjectivity is a property that can be associated with word senses, and (2) word sense disambiguation can directly benefit from subjectivity annotations. | Word Sense and Subjectivity Janyce Wiebe Department of Computer Science University of Pittsburgh wiebe@cs.pitt.edu Rada Mihalcea Department of Computer Science University of North Texas rada@cs.unt.edu Abstract Subjectivity and meaning are both important properties of language. This paper explores their interaction and brings empirical evidence in support of the hypotheses that 1 subjectivity is a property that can be associated with word senses and 2 word sense disambiguation can directly benefit from subjectivity annotations. 1 Introduction There is growing interest in the automatic extraction of opinions emotions and sentiments in text subjectivity to provide tools and support for various NLP applications. Similarly there is continuous interest in the task of word sense disambiguation with sense-annotated resources being developed for many languages and a growing number of research groups participating in large-scale evaluations such as Senseval. Though both of these areas are concerned with the semantics of a text over time there has been little interaction if any between them. In this paper we address this gap and explore possible interactions between subjectivity and word sense. There are several benefits that would motivate such a joint exploration. First at the resource level the augmentation of lexical resources such as WordNet Miller 1995 with subjectivity labels could support better subjectivity analysis tools and principled methods for refining word senses and clustering similar meanings. Second at the tool level an explicit link between subjectivity and word sense could help improve methods for each by integrating features learned from one into the other in a pipeline approach or through joint simultaneous learning. In this paper we address two questions about word sense and subjectivity. First can subjectivity labels be assigned to word senses To address this question we perform two studies. The first Section 3 investigates agreement between .