Translation by Structural Correspondences
What it is about
The paper proposes machine translation without a transfer program. The source and target sentences are described by LFG structures at several levels (constituent, functional, semantic), and the translation is a set of correspondence functions between those structures. The functions are written as equations, so the mapping can depend on information from several levels at once, and both grammars and lexicons stay modular. The authors show the method with English, German and French examples where the source and target analyses differ in structure. The paper is a sketch of the approach; it has no evaluation.
Ideas
- I1. Store the author delta as a set of partial correspondences between the features of meta tokens, not as a procedure. Each override names a source feature, a target feature and a condition, and the encoder solves the set. Conflicts between overrides are then counted rather than hidden by order.
- I2. Use two levels at once: keep the UD relation and the frame role on each meta token, and learn the correspondence from role to target relation (for example, subject to subject) from aligned verses. Count how often one role maps to one relation in each author pair.
- I3. Measure which residual class the missing correspondences cause: if a verse fails only because a role has no mapping, the error belongs to the mapping, not to the reader or the encoder. Report the count per class each run, twice, for determinism.
For Mova
The code is tools/translate (meta.rs, profile.rs) with the roles of prag. The paper is not a method Mova should copy, since its equations are hand-written, but the idea of several simultaneous levels with partial mappings is the form the open problems 1 and 3 ask for.
Cite
@inproceedings{kaplan1989translation,
title = {{Translation by Structural Correspondences}},
author = {Kaplan, Ronald M. and Netter, Klaus and Wedekind, Jurgen and Zaenen, Annie},
booktitle = {Fourth Conference of the European Chapter of the Association for Computational Linguistics},
year = {1989},
url = {https://aclanthology.org/E89-1037/}
}References
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