Unni Cathrine Eiken February 2005

In the introduction to this chapter, it was stated that the aim of classifying the EPAS list is
twofold; on the one hand it is of interest to see to which degree the environments that an
argument occurs in over a collection of texts provide sufficient cues to ensure a correct guess of
which argument can be expected in a specific context, on the other hand it is equally interesting
to see if we through classification can narrow down the set of possible arguments for a specific
context pattern. Through the association technique, six groups of words emerged; the members
of each group sharing the feature that they all tend to occur in the same environments.
Previously, it has been stated that some anaphors need access to information about the world in
order to be resolved. This information can to some extent be represented by the concept groups
associated from the data set. By identifying groups of words which typically occur in the same
textual environment, an intuition about which words to expect in which contexts is captured. In
the event of “difficult” anaphors which depend on world knowledge, an anaphora resolution
system can retrieve potential antecedents from the text, check which concept group an expected
antecedent is likely to belong to and consequently chose the antecedent candidate belonging to
the expected concept group. As a first step of examining the usefulness of concept groups in
combination with anaphora, experiments aiming at enhancing the performance of the classifier
in section 4.1 were performed. These experiments are described in the following section.
4.3.1 Testing
Tests were performed in TiMBL, using the relevant concept group as the category for a feature
pattern. Analogous to the testing in section 4.1.2 above, two separate test sets were prepared,
one for the classification of each argument. In the cases where the relevant argument was a
member of one of the concept groups, the head label of the concept group was used as the
category label in the input data. If the relevant argument did not belong to any concept group,
the argument itself was used as category label, as in the tests in section 4.1.2. Example (4-12)
below shows an excerpt of the input file used for training the classifier for argument 1
classification.
(4- 12)
drepe,gjerningsmann,kvinne,PERP
drept,sykepleiestudent,?,WOMAN
død,sykepleiestudent,?,WOMAN
ekstra,patrulje,?,patrulje
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