Zero-subject Resolution by Probabilistic Model

Abstract

Probabilistic resolution method for Japanese zero-subjects is described. It is designed to be used for the back-end processor of an automatic shortening system of long Japanese sentences in a Japanese to English machine translation system. Ordinary probabilistic resolution method uses (1) normal distribution model in the continuous probability space. In this article, we propose 3 new models. They are (2) quasi-normal distribution model in the continuous space,(3) 1st order log-linear distribution model in the discrete space and (4) 2nd order log-linear distribution model in the discrete space. For these four models, we make an experiment to measure the resolution accuracy. The test sample is from television broadcasting news. The measured accuracy by the cross validation test are 73%, 78%, 78% and 81% for (1), (2),(3) and (4) models, respectively. The unresolved examples show that semantic agreement between subject and predicate should be observed more accurately.

Japanese zero pronoun resolution based on ranking rules and machine learning

“…Since complex sentences are hard to analyze, each sentence is automatically split at conjunctive postpositions (setsuzoku joshi) (Okumura and Tamura, 1996;Ehara and Kim, 1996). In order to distinguish the original complex sentence and the simpler sentences after the split, we call the former just a 'sentence' and the latter 'post-split sentences'.…”

“…4. Demotion of candidates in a relative clause (rentai shuushoku setsu): Usually, Japanese zeros do not refer to noun phrases in relative clauses (Ehara and Kim, 1996). (See Appendix B for details.…”

“…' Most studies on Japanese zero pronoun resolution have not tried to resolve zeros in full-text newspaper articles. They have discussed simple sentenses (Kameyama, 1986;Walker et al, 1994;Yamura-Takei et al, 2002), dialogues (Yamamoto et al, 1997), stereotypical lead sentences of newspaper articles (Nakaiwa and Ikehara, 1993), intrasentential resolution (Nakaiwa and Ikehara, 1996;Ehara and Kim, 1996) or organization names in newspaper articles (Aone and Bennett, 1995).…”