英文摘要 |
A meaningful noun-verb word-pair in a sentence is called a noun-verb event-frame (NVFE). Previously, we have developed an NVEF word-pair identifier to demonstrate that NVEF knowledge can be used effectively to resolve the Chinese word-sense disambiguation (WSD) problem (with 93.7% accuracy) and the Chinese syllable-to-word (STW) conversion problem (with 99.66% accuracy) on the NVEF related portion. In this paper, we propose a method for automatically acquiring a large scale NVEF knowledge without human intervention. The automatic discovery of NVEF knowledge includes four major processes: (1) segmentation check; (2) Initial Part-of-speech (POS) sequence generation; (3) NV knowledge generation and (4) automatic NVEF knowledge confirmation. Our experimental results show that the precision of the automatically acquired NVEF knowledge reaches 98.52% for the test sentences. In fact, it has automatically discovered more than three hundred thousand NVEF word-pairs from the 2001 United Daily News (2001 UDN) corpus. The acquired NVEF knowledge covers 48% NV-sentences in Academia Sinica Balanced Corpus (ASBC), where an NV-sentence is one including at least a noun and a verb. In the future, we will expand the size of NVEF knowledge to cover more than 75% of NV-sentences in ASBC. We will also apply the acquired NVEF knowledge to support other NLP researches, in particular, shallow parsing, syllable/speech understanding and text indexing. |