---
title: "Machine Translation with Many Manually Labeled — Meyer 2013"
description: "Explicit discourse connectives such as while , as or meanwhile are hard for sentence-level SMT."
authors: ["Thomas Meyer", "Lucie Poláková"]
year: 2013
venue: "Proceedings of the Workshop on Discourse in Machine Translation"
source: "https://aclanthology.org/W13-3306/"
licence: "CC BY-NC-SA 3.0 (ACL Anthology, before 2016)"
licence_url: "https://creativecommons.org/licenses/by-nc-sa/3.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/papers/meyer-2013-machine-translation-many-manually-labeled/"
---
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# Machine Translation with Many Manually Labeled Discourse Connectives

**Authors:** [Thomas Meyer](https://md.research.elamur.ai/free/authors/thomas-meyer/), [Lucie Poláková](https://md.research.elamur.ai/free/authors/lucie-polakova/) · **Year:** 2013 · **Venue:** Proceedings of the Workshop on Discourse in Machine Translation · **Licence:** [CC BY-NC-SA 3.0 (ACL Anthology, before 2016)](https://creativecommons.org/licenses/by-nc-sa/3.0/)

**Links:** [Publisher's page](https://aclanthology.org/W13-3306/) · [PDF](https://aclanthology.org/W13-3306.pdf) · [OpenAlex](https://openalex.org/W91670896)

**Citations:** 15 citations (openalex-snapshot · 2026-10-14) · [9](#cited-by) in our library, of the 140673 papers whose bibliographies we read

## Summary
Explicit discourse connectives such as *while*, *as* or *meanwhile* are hard for sentence-level SMT. One English form can signal several relations, and Czech may need a different connective, or even a different construction, for each one. Earlier English/French work used automatic classifiers that mislabel many instances. This paper instead uses gold-standard PDTB sense labels on the parallel PCEDT. That treebank pairs the Wall Street Journal texts with a human Czech translation, so manual relation labels for about 100 connective types can be fed straight into an EN→CZ system. The authors trained phrase-based Moses models in which each English connective is joined to its sense tag. One variant keeps the full tags and another keeps simplified tags; both are compared with an unlabeled baseline. Automatic scores were stable. For some ambiguous connectives, gains ranged from 4% to 60%, and the labels sometimes helped produce the right Czech syntax, such as a clause instead of a prepositional phrase. Manual analysis showed that labeling every connective is unnecessary. Only a handful of highly ambiguous ones (*as*, *when*, *while*, *yet*) really benefit.

## Key points
- **Data:** PCEDT 2.0 provides about 50k sentence-aligned EN/CZ sentences (WSJ sections 00–24). PDTB 2.0 contributes 18,459 manually annotated explicit connectives, with senses organized in a three-level hierarchy (4/16/23 classes) and up to 129 possible tags. Europarl EN/CZ was added to obtain enough training data.
- **Systems:**
  - SYSTEM 1 uses the full PDTB tags, giving 63 observed sense tags.
  - SYSTEM 2 keeps only levels 1–2 and drops composite senses, giving 22 tags.
  - Both are compared with a BASELINE trained on the same text without labels.
- **Evaluation:** Testing used PDTB section 23. BLEU was averaged over 5 MERT runs and checked with t-tests.
- **Manual comparison (SYSTEM 2 vs. BASELINE):** On a sample of 630 labeled connectives, 8.2% of translations improved and 4.0% got worse, with the rest equal, once a recurring *but–jenže* case is excluded. For the connective *as*, SYSTEM 2 was better in 68% of 25 instances.
- **Future work:** The authors plan factored translation models and want to select which connectives, and at what sense granularity, are worth labeling.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

Fields: [Linguistics & languages](https://md.research.elamur.ai/free/shelves/linguistics/)

Topics: [Discourse analysis](https://md.research.elamur.ai/free/topics/discourse-analysis/) · [Machine translation](https://md.research.elamur.ai/free/topics/machine-translation/)

## Cited by

Cited by

9 papers of our library cite it (of the 140673 whose bibliographies we read); 2 of them have a page here, 7 not yet.

- [ParCor 1.0: A Parallel Pronoun-Coreference Corpus to Support Statistical MT](https://md.research.elamur.ai/free/papers/guillou-2014-parcor-1-0-parallel-pronoun/)
- [Discourse Structure in Machine Translation Evaluation](https://md.research.elamur.ai/free/papers/joty-2017-discourse-structure-machine-translation-evaluation/)

## Cite

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{meyer2013machine,
  title = {{Machine Translation with Many Manually Labeled Discourse Connectives}},
  author = {Meyer, Thomas and Poláková, Lucie},
  booktitle = {Proceedings of the Workshop on Discourse in Machine Translation},
  year = {2013},
  url = {https://aclanthology.org/W13-3306/}
}
```

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