Unni Cathrine Eiken February 2005

(1- 5)
predicate, argument 1, argument 2
In the classification phase, the extracted structures undergo processes that result in the grouping
of concepts into clusters of semantically similar words.
The evaluation of the results obtained by using the method developed in the project is twofold:
• the resulting concept classes are evaluated; does the method produce semantic clusters
that are valid for the thematic domain of the text collection?
• the usefulness of using the concept classes in anaphora resolution is evaluated; does the
method provide a means to infer which entity is referred to in examples such as (1-1)
and (1-2)?
Chapter 3 describes the extraction method, which uses output from a syntactic parser to collect
semantic structures in the form of EPAS from the texts. The text collection used in this project
consists of newspaper texts all concerning a criminal case. The constraints that hold on the
corpus are further described in sections 3.1 and 3.4. Section 3.2 explains the format of the
meaning structures extracted from the text corpus as well as the motivation for choosing EPAS
as meaning representation. In sections 3.3 and 3.5 the process of parsing the texts and gathering
the meaning representations from the parse output is outlined in further detail. Finally, the list of
EPAS resulting from the extraction method is evaluated in section 3.6.
The classification method is described in chapter 4. In section 4.1 a classification approach using
machine learning techniques is described, in section 4.2 the constituents of the EPAS are
associated into semantically similar groups based on their contextual distribution and finally
these two approaches are applied in connection with one another in section 4.3. In section 4.4
the potential of using concept groups in anaphora resolution is discussed.
Final remarks and conclusions are found in section 5. Here the foundation of the extraction
method is also briefly discussed.
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