Unni Cathrine Eiken February 2005

c. PERP:
gjerningsmann, drapsmann
perpetrator, killer
d. PERSON:
person, bilfører, syklist, vedkommende
person, car driver, biker, generic-nom
e. OBSERV:
teori, observasjon
theory, observation
f. PLACE:
studentkollektiv, Førde
student housing, Førde
The classes of words shown in (4-11) form groups of concepts which occur in the same
contextual environments within the thematic domain that the EPAS are extracted from. The
groupings seem to reflect real semantic clusters in the sense that one can easily find a label to
describe each group. For the purpose of the text collection in the present work, these six concept
groups represent six distinct semantic groupings that share many features with respect to pattern
distribution in the data set. With a larger data set to run the concept association on, more concept
groups, and also more members within each group, would have been a likely outcome. The
results of the concept association on the small data set in this project, does, however, suggest the
feasibility of the method, as well as show that frequent patterns in smaller text collections also
work toward capturing interesting concept groupings.
4.3 Step III: Using concept groups in TiMBL
The concept groups which emerged as a result of the association performed in section 4.2 above,
represent clusters of words that occur in similar constellations in the data material. The
emergence of concept groups which intuitively seem to have some semantic resemblance to
each other confirms that the context a word fits into does indeed say something about what the
word means, as per the distributional hypothesis.
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