Unni Cathrine Eiken February 2005

Training and testing the classifier on the EPAS_arg2 list with no pronouns produced an accuracy
of 49,73%. As was the case for the corresponding classification of argument 1, it is likely that
the relatively small dataset is a disadvantage for the classification process.
4.1.3 Comments on the results
The results obtained through classifying the EPAS indicate that the information present in the
EPAS derived from the text collection does provide clues about which word to expect in a
specific position. The accuracy scores obtained by training and testing on the EPAS extracted
from a collection of texts suggest that even a small collection of texts on the same domain
provide information to enable a classification approach based on contextual distribution. In the
tests described above, there was a reoccurring tendency that in a number of the cases where the
wrong category was assigned in the test phase, the assigned category bore some semantic
resemblance to the correct category. This reinforces the initial intuition that similar words are
used in similar environments and that the environment can contribute with clues toward the
semantic meaning of a word.
In the following section, the notion of finding words which are similar to each other by virtue of
occurring in the same environments will be explored further.
4.2 Step II: Association of concept groups
The fundamental idea in this thesis is that words display certain semantic features based solely
on the context they are found in. Therefore, when looking for possible antecedents for an
anaphoric expression, the candidates should not only be weighted according to their cooccurrence
in an identical context pattern in a corpus, but also according to their co-occurrence
with similar context patterns. The assumption that words which occur in identical contexts have
related meanings can be used to retrieve words with similar meanings from the data material.
With a target argument and a target predicate as starting point, the association method goes
through the EPAS list and returns words which occur in similar environments to the target
argument. This association is performed in three steps:
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