<?xml version="1.0" standalone="yes"?>
<Paper uid="P97-1045">
  <Title>Automatic Extraction of Aspectual Information from a Monolingual Corpus</Title>
  <Section position="6" start_page="357" end_page="358" type="relat">
    <SectionTitle>
4 Related Work
</SectionTitle>
    <Paragraph position="0"> The approach proposed here is similar to that of Dorr's (Dorr, 1992: Dorr. 1993), but different from it in scale and determinability of the categories. She adopts the four-way classification system following Vendler (Vendler, 1957) and utilizes Dowty's test (Dowty, 1991) for deternfining aspectual categories of English verbs. She reports the results obtained from running the program on 219 sentences of the LOB corpus. Although we cannot know how many verbs she tested because she has shown only a subset of the verbs, the program was not able to pare down the aspectual category to one in 18 cases out of 27 verbs.</Paragraph>
    <Paragraph position="1"> Brent (Brent, 1991) discusses an implemented program that automatically classifies verbs into two groups, stative vs. non-stative, on the basis of their syntactic contexts. He uses the progressive and rate- null ambiguous 14 12 9 64 75 total 200 200 142 71 71 adverbs constructions in combination with some sort of statistical smoothing technique. He identified eleven verbs as purely stative, of the 204 distinct verbs occurring at least 100 times in the LOB corpus. null We think that the extraction of aspectual information must be based on principles that are well-grounded in linguistic theory. However, some sort of noise reduction technique such as the confidence intervals used by Brent may be needed to detect the cue more accurately.</Paragraph>
  </Section>
class="xml-element"></Paper>