GWC 2008

Verification of Valency Frame Structures by Means of
Automatic Context Clustering in RussNet
Irina V.Azarova 1 , Anna S. Marina 2 , and Anna A. Sinopalnikova 3
1 Department of Applied Linguistics, St-Petersburg State University, Universitetskaya nab.
11, 199034 St-Petersburg, Russia.
2 Department of Lexicography, Institute of Linguistic Studies, Tuchkov pereulok 9, 199053
Saint-Petersburg, Russia.
3
Brno University of Technology, Bozetechova 2, 61266 Brno, Czech
ivazarova@gmail.com, a_s_marina@rambler.ru, sino@fit.vutbr.cz
Abstract. The major point of the RussNet technique is a specification of
valency frames for synsets. Parameters of valency frames are employed for
word meaning and synsets differentiating in the procedure of thesaurus
construction and automatic text analysis for word disambiguation. Valency
description is calculated on the basis of statistically stable context features in
the text corpus: morphologic, syntactic, and semantic. The automatic
classification of verb contexts with unambiguous morphology annotation is
discussed in the paper. The goal of this technique is differentiation of semantic
types for verbs. The procedure is fulfilled with a help of morphology tag
distributions in some context window for verbs from different semantic trees of
RussNet. The optimal width of a distribution window, an appropriate tag set,
and clustering results are discussed. This procedure may be helpful at various
stages of analysis, especially for valency frame verification in some semantic
tree.
1 Introduction
The computer thesaurus RussNet1 developed at the Department of Applied
Mathematic Linguistics of Saint-Petersburg State University inherited the main
principles of WordNet construction method [1]. RussNet is based on the corpus of
modern texts (dated from 1985 up to nowadays) including 21 million of words, the
major part of which (60%) are articles on various topics from newspapers and
magazines, covering thematic diversity of the common Russian language [2].
The RussNet was not translated from the WordNet prototype, its construction
involves some additional components in its structure, that were oriented to its usage in
automatic text analysis [3].
The basic node in RussNet – the synset – may include several members (words or
multiword expressions), which are ordered by their frequency of appearance in the
corpus contexts in the particular sense described by the synset. This frequency is
1
http://www.phil.pu.ru/depts/12/RN