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# Towards Heterogeneous Automatic MT Error Analysis

**Authors:** Jesús Giménez, [Lluís Màrquez](https://md.mova.elamur.ai/free/en/docs/papers/authors/lluis-marquez/) · **Year:** 2008 · **Venue:** Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC 2008) **Link:** [aclanthology.org/L08-1145](https://aclanthology.org/L08-1145/) · **Licence:** [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) — summary only

[**10** citations](https://openalex.org/works?filter=cites:W184114328) openalex · 2026-10-19[**3** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/gimenez-2008-heterogeneous-automatic-mt-error-analysis/) of the 140673 papers whose bibliographies we read[Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)](https://aclanthology.org/volumes/L08-1/)[licence](https://creativecommons.org/licenses/by-nc/4.0/)

- [Publisher's page](https://aclanthology.org/L08-1145/)
- [PDF](https://aclanthology.org/L08-1145.pdf)
- [DOI 10.63317/3fq8iorodjww](https://doi.org/10.63317/3fq8iorodjww)
- [OpenAlex](https://openalex.org/W184114328)

**Authors (2)**

1. [Jesús Giménez](https://openalex.org/A5112552818) [Semantic Scholar](https://www.semanticscholar.org/author/36924412) · h 14 · 1117 citations · 39 works
2. [Lluís Màrquez](https://openalex.org/A5103372090) [Semantic Scholar](https://www.semanticscholar.org/author/66994096) · h 45 · 8248 citations · 203 works

Citations and author metrics from openalex (2026-10-19); authors with the same name are not always told apart.

## What it is about

The paper argues that automatic MT metrics should be used for error analysis, not only for a single score. It compiles a set of metric variants at five linguistic levels: lexical (WER, PER, BLEU, NIST, GTM, ROUGE, METEOR), shallow syntax, dependency and constituency overlap, shallow semantics (named entities and semantic roles), and discourse representations. The variants are computed in the IQMT framework. The case study uses the NIST 2005 Arabic–English test set, with one human-aided system and the best statistical system. Surface metrics prefer the statistical system, while deeper metrics give rankings closer to human judgments. Reports are produced at document and sentence level, showing at which level a system loses. There is no formal study of how reliable the reports are.

## Ideas

- I1. A level profile for each translator output: score it per level (concept, tag, head and relation, frame role, word order) and print the level where the score falls. The profile replaces one residual number with a short diagnosis.
- I2. Keep the paper's warning as a rule. When a translator variant improves the exact-match score but not the frame-level score, the surface gain is flagged. A delta is kept only if the deeper-level score also improves.
- I3. A dependency-overlap score for subject and object pairs, computed on the meta trees of two readings of one verse. It measures open problem 1 directly: do the two readings agree on the heads?

## For Mova

The places are `tools/translate/src/measure.rs`, `tools/roundtrip` (frames), `prag` (roles) and `tools/macula` (Hebrew trees). The metric variants themselves are not needed, since Mova's frames are deterministic. What carries over is the level-by-level report. Nothing here has been tried in Mova.

Topics: [Machine translation](https://md.mova.elamur.ai/free/en/docs/papers/topics/machine-translation/)

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.63317/3fq8iorodjww](https://doi.org/10.63317/3fq8iorodjww)

```
@inproceedings{gimenez2008heterogeneous,
  title = {{Towards Heterogeneous Automatic MT Error Analysis}},
  author = {Giménez, Jesús and Màrquez, Lluís},
  booktitle = {Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)},
  year = {2008},
  doi = {10.63317/3fq8iorodjww},
  url = {https://doi.org/10.63317/3fq8iorodjww}
}
```

- [← previous Rule-based Surface Realization of Romanian Weak Pronouns](https://md.mova.elamur.ai/free/en/docs/papers/gerstenberger-2025-rule-based-surface-realization-romanian/)
- [next → Feature-Rich Translation by Quasi-Synchronous Lattice Parsing](https://md.mova.elamur.ai/free/en/docs/papers/gimpel-2009-feature-rich-translation-quasi-synchronous/)
- [↑ back to Machine translation](https://md.mova.elamur.ai/free/en/docs/papers/mtrans/)

## References

27 references, 4 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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