Nowadays event extraction systems mainly deal with a relatively small amount of
information about temporal and modal qualifications of situations, primarily
processing assertive sentences in the past tense. However, systems with a wider
coverage of tense, aspect and mood can provide better analyses and can be used in a
wider range of text analysis applications. This thesis develops such a system for
Turkish language. This is accomplished by extending Open Source Information
Mining and Analysis (OPTIMA) research group' / s event extraction software, by
implementing appropriate extensions in the semantic representation format, by
adding a partial grammar which improves the TAM (Tense, Aspect and Mood)
marker, adverb analysis and matching functions of ExPRESS, and by constructing an
appropriate lexicon in the standard of CORLEONE. These extensions are based on
iv
the theory of anchoring relations (Temü / rcü / , 2007, 2011) which is a cross-
linguistically applicable semantic framework for analyzing tense, aspect and mood
related categories. The result is a system which can, in addition to extracting basic
event structures, classify sentences given in news reports according to their temporal,
modal and volitional/illocutionary values. Although the focus is on news reports of
natural disasters, disease outbreaks and man-made disasters in Turkish language, the
approach can be adapted to other languages, domains and genres. This event
extraction and classification system, with further developments, can provide a basis
for automated browsing systems for preventing environmental and humanitarian risk.
Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12614300/index.pdf |
Date | 01 April 2012 |
Creators | Hurriyetoglu, Ali |
Contributors | Ceyhan, Temurcu |
Publisher | METU |
Source Sets | Middle East Technical Univ. |
Language | English |
Detected Language | English |
Type | M.A. Thesis |
Format | text/pdf |
Rights | To liberate the content for public access |
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