Are Ellipses Important for Machine Translation?

What it is about

The paper tests how much ellipsis hurts neural machine translation, from English into Hindi and Telugu. It uses 1,500 sentences: 500 each of nominal, verbal and clausal ellipsis, taken from the Bos and Spenader VPE corpus, a curated ellipsis set and other annotated corpora. Each sentence is also given in a version with the ellipsis reconstructed. Manual labels show that 1,066 of 1,500 Hindi translations and 1,201 Telugu translations are poor, so over 70% are poor in both languages. Most errors fall in the clause that holds the ellipsis, and Telugu has more of them. Reconstructing the ellipsis improves adequacy, mostly for noun and verb ellipses, at some cost in fluency.

Ideas

I1. en/src/lin.rs: after the generator writes a sentence from a tree with an elided verb or noun, check that the output has the full verb or head. Count such failures on EWT test. This is a generation check, not a translation claim, and it needs no outside model.
I2. Offline labels: a large model may label ellipsis types for an annot set, offline, and a person checks 100 of them before use. It may never answer at test time. The paper's three-type split is a good scheme for such a set.
I3. Error-type report: in en explain, tag each generation error as a missing-clause error or a missing-head error, so that the clause with the ellipsis is named in the output.

For Mova

The code is en/src/lin.rs, en/src/ctx.rs and annot. The chapter is 29. Ellipsis, word order and information structure. Mova has no translation step, so the MT results are not Mova results; only the generation check and the labelling ideas carry over. The paper is CC BY-NC-ND, so it is summarised here and not quoted at length. Measure first: the generation check on EWT test.

Topics: Machine translation

Cite

The paper itself, not this card. BibTeX from the library's record of the work. DOI 10.1162/coli_a_00414

@article{khullar2021are,
  title = {{Are Ellipses Important for Machine Translation?}},
  author = {Khullar, Payal},
  journal = {Computational Linguistics},
  year = {2021},
  doi = {10.1162/coli\_a\_00414},
  url = {https://doi.org/10.1162/coli_a_00414}
}

References

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