Investigating the Characteristics of Causal Relations in Japanese Text

Proceedings of the Workshop on Frontiers in Corpus Annotation II: Pie in the Sky, pages 37–44, Ann Arbor, June 2005. c⃝2005 Association for Computational Linguistics Investigating the Characteristics of Causal Relations in Japanese Text Takashi Inui and Manabu Okumura Precision and Intelligence Laboratory Tokyo Institute of Technology 4259, Nagatsuta, Midori-ku, Yokohama, 226-8503, Japan tinui@lr.pi.titech.ac.jp, oku@pi.titech.ac.jp Abstract We investigated of the characteristics of in-text causal relations. We designed causal relation tags. With our designed tag set, three annotators annotated 750 Japanese newspaper articles. Then, using the annotated corpus, we investigated the causal relation instances from some view- points. Our quantitative study shows that what amount of causal relation instances are present, where these relation instances are present, and which types of linguistic expressions are used for expressing these relation instances in text. 1 Introduction For many applications of natural language tech- niques such as question-answering systems and di- alogue systems, acquiring knowledge about causal relations is one central issue. In recent researches, some automatic acquisition methods for causal knowledge have been proposed (Girju, 2003; Sato et al., 1999; Inui, 2004). They have used as knowledge resources a large amount of electric text documents: newspaper articles and Web documents. To realize their knowledge acquisition methods accurately and efficiently, it is important to know- ing the characteristics of presence of in-text causal relations. However, while the acquisition methods have been improved by some researches, the char- acteristics of presence of in-text causal relations are still unclear: we have no empirical study about what amount of causal relation instances exist in text and where in text causal relation instances tend to ap- pear. In this work, aiming to resolve the above issues, we create a corpus annotated with causal relation information which is useful for investigating what amount of causal relation instances are present and where these instances are present in text. Given some Japanese newspaper articles, we add our de- signed causal relation tags to the text segments. Af- ter creating the annotated corpus, we investigate the causal relation instances from three viewpoints: (i) cue phrase markers, (ii) part-of-speech information, and (iii) positions in sentences. There are some pieces of previous work on anal- ysis of in-text causal relations. However, although causal relation instances appear in several different ways, just a few forms have been treated in the pre- vious studies: the verb phrase form with cue phrase markers such as in (1a) has been mainly treated. In contrast, we add our causal relation tags to several types of linguistic expressions with wide coverage to realize further analyses from above three points. Ac- tually, we treat not only linguistic expressions with explicit cues such as in (1a) , but also those with- out explicit cues, i.e. implicit, as in (1b) , those formed by noun phrases as in (1c), and those formed between sentences as in (1d) . (1) a. �� - � �� - � �� - � �  - � heavy rain-NOM fall-PAST because river-NOM rise-PAST (explicit) b. �� - …

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