Unni Cathrine Eiken February 2005

3 From text to EPAS – the extraction method
This chapter describes the extraction method used in this project. The method extracts EPAS
(elementary predicate-argument structures) from a text corpus consisting of newspaper texts
collected from the internet.
3.1 Selecting the texts
Specifying the requirements for a suitable text collection is not as trivial as it may seem. To
make sure that the extracted EPAS would produce semantically valid results when classified, the
texts from which the structures were extracted had to fulfil certain requirements. Since the
classification builds on the distributional hypothesis and relies on EPAS which show distribution
particular to a restricted domain, initially, the most important specification for the texts was that
they all had to belong to the same thematic domain. As such, the main focus in the requirements
specification for the text collection was that of one closed thematic domain. But how exactly
does one define the notion of a thematic domain? The first test set collected for the project
consisted of factual prose texts dealing with roughly the same field. These texts, however,
proved to be quite unsuitable for the later analysis, for reasons that will be explained in the
following.
It is clear that certain specifications must be fulfilled in the text collection from which the EPAS
are derived. Texts displaying longer discourse chains are most suitable for the purpose of this
project. One thematic domain must be described over several paragraphs, or preferably over the
entire course of the discourse in the text. In order to extract the desired information from the
texts and subsequently test if useful information has been extracted, the presence of anaphora, or
referring expressions, in the text is needed. This entails the need for pronouns in particular. As
such, texts containing discourse with a certain amount of concrete content were particularly
useful for my purpose.
Texts that are too vague, both with regards to their textual content and to their membership in a
particular thematic category, were not suitable for the purpose of this project because they do
not contain the type of theme-specific selectional constraints we are interested in extracting. One
reoccurring problem in the text collections tested for the project was a too small degree of
information expressed in full text, and very much information present in bullet lists, tables and
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