IMPLICIT LOGICAL-SEMANTIC RELATIONS AND A METHOD OF THEIR IDENTIFICATION IN PARALLEL TEXTS

One of the main characteristics of logical-semantic relations (LSRs) between two fragments of a text is that these relations can be either explicit (expressed by some marker, e.g. a connective) or implicit (derived from the interrelation of these fragments’ semantics). Since implicit LSRs do not have any marker, it is difficult to find them in a text (whether automatically or not). In this paper, approaches to analysing implicit LSRs are compared, an original definition for them is offered and differences between implicit LSRs and LSRs expressed by non-prototypical means are described. A method is proposed to identify implicit LSRs using a parallel corpus and a supracorpora database of connectives. Based on the well-known statement that LSRs can be explicitated by adding connectives in the translation, it is argued here that through selecting pairs in which fragments where a connective is used to express an LSR in the translation correspond to those containing any of the translation stimuli standard for this connective in the source language, it is possible to get an array of contexts in which this LSR is implicit in the source text (or expressed by means other than connectives). This method is then applied to study the French causal connectives car, parce que and puisque using a Russian-French parallel corpus. The corpus data are analysed to obtain information about LSRs particularly about cases where the causal LSR in Russian is implicit, as well as about the use of causal connectives in French. These results are used to show that the method proposed allows to quickly create a representative array of contexts with implicit LSRs, which can be useful in both text analysis and in machine learning.