Subclassification of Parts of Speech in Russian: Verbs

2 " 196 5 International Conference on Computational Linguistics" SUBCLASSIFICATION OF PARTS OF SPEECH IN RUSSIAN: VERBS ~ A. Andreyewsky Inte rnatlonal Busine s s Machine s Corporation Thomas 3. Watson Research Center P. O. Box Z18 Yorktown Heights, New York, 10598 /,.~'.,~ .... ".'.,..-,~ \ • Thls work was partly sponsored by the Information Processing Laboratory, Rome Air Development Center, United States Air Force, under Contract AF 30(60Z)-3301 Andreyewsky I Abstract In a trial study, about 500 Russian verbs were coded using 44 potential classificatory criteria. Through sorting and the introduction of a metric, numerous groupings were obtained. Initial results suggest that, with proper refinements, the approach described cab provide use- ful information that may be employed in syntactic analysis and certain information retrieval applications. 0. 0 Introduction As part of a broader effort to extend the existing traditional part- of-speech classification in modern Russian, this study of verbs is oriented toward developing an improved basis for syntactic analysis. Moreover, it is hoped that the refinements introduced will be of interest in content analysis. To this end, an extensive set of potential classificatory cri- teria has been selected, in the hope that eventually this categorization can be optimized and extended to other parts of speech. I. 0 The Experiment The 514 verbs analyzed came from two sources: (a) a randomized sample of 370 entries ( I ) and (b) a list of the most frequently used Russian verbs ( Z ) from which the first 144 entries were selected. The classificatory criteria, subdivided into two groups, are discussed in Section I. 1 below. Generally, each verb was taken in a particular meaning (stirat', for instance, as "to erase" and not as "to launder") and English equivalents used solely for purposes of identifica- tion. At the same time, for reasons of convenience, provisions were made in coding to allow for coexisting alternatives. Thus, for proper- ties A and B there can be four posBibilities which are represented by the following numerical codes: i - "A", Z - "B", 3 - "AB", 0 - "neither applle s" After the verbs and appropriate codes were punched on cards, verbs with identical codes were compared. To obtain additional cluster- ing, a program, written by R. F. Hubbard for the IBM 7040, compared the code vector of each card against those of the rest of the sample. The distance between any two entries was calculated by taking the square root of the sum of the squares of distance between correspond- ing positions in their code vectors as defined by the following table: Andreyewsky 2 0--0 = 0 0--2= 4 I~i : 0 I~3 = i 2~3 = i 0--I=40--3:6 l~Z=2 Z--2=03~3:0 i. i Tests Since one of the main objectives of this study has been to estab- lish the relevance of various classificatory criteria, these were tested in two groups as described below. The selection of criteria, based on studies of existing grammars of Russian, was directed toward discov- ering solutions for problems arising …

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