<?xml version="1.0" standalone="yes"?>
<Paper uid="P06-1145">
  <Title>Sydney, July 2006. c(c)2006 Association for Computational Linguistics Time Period Identification of Events in Text Taichi Noro + Takashi Inui ++ Hiroya Takamura ++</Title>
  <Section position="4" start_page="1153" end_page="1153" type="relat">
    <SectionTitle>
2 Related Work
</SectionTitle>
    <Paragraph position="0"> The task of time period identification is new and has not been explored much to date.</Paragraph>
    <Paragraph position="1"> Setzer et al. (2001) and Mani et al. (2000) aimed at annotating newswire text for analyzing temporal information. However, these previous work are different from ours, because these work only dealt with newswire text including a lot of explicit temporal expressions.</Paragraph>
    <Paragraph position="2"> Tsuchiya et al. (2005) pursued a similar goal as ours. They manually prepared a dictionary with temporal information. They use the hand-crafted dictionary and some inference rules to determine the time periods of events. In contrast, we do not resort to such a hand-crafted material, which requires much labor and cost. Our method automatically acquires temporal information from actual data of people's activities (blog).</Paragraph>
    <Paragraph position="3"> Henceforth, we can get temporal information associated with your daily life that would be not existed in a dictionary.</Paragraph>
  </Section>
class="xml-element"></Paper>