Extracting Noun Phrases from Large-Scale Texts: A Hybrid Approach and Its Automatic Evaluation

To acquire noun phrases from running texts is useful for
many applications, such as word grouping, terminology
indexing, etc. The reported literatures adopt pure
probabilistic approach, or pure rule-based noun phrases
grammar to tackle this problem. In this paper, we apply
a probabilistic chunker to deciding the implicit
boundaries of constituents and utilize the linguistic
knowledge to extract the noun phrases by a finite state
mechanism. The test texts are SUSANNE Corpus and
the results are evaluated by comparing the parse field of
SUSANNE Corpus automatically. The results of this
preliminary experiment are encouraging.