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# Rule-based Surface Realization of Romanian Weak Pronouns

**Authors:** Ciprian Gerstenberger · **Year:** 2025 · **Venue:** Proceedings of the 9th Workshop on Constraint Grammar and Finite State NLP **Link:** [aclanthology.org/2025.cgmta-1.2](https://aclanthology.org/2025.cgmta-1.2/) · **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)

[Proceedings of the 9th Workshop on Constraint Grammar and Finite State NLP](https://aclanthology.org/volumes/2025.cgmta-1/)[licence](https://creativecommons.org/licenses/by/4.0/)

- [Publisher's page](https://aclanthology.org/2025.cgmta-1.2/)
- [PDF](https://aclanthology.org/2025.cgmta-1.2.pdf)

**Authors (1)**

1. Gerstenberger, Ciprian

Citations and author metrics from OpenAlex (); authors with the same name are not always told apart.

## What it is about

Romanian weak pronouns, the clitics, take many surface forms that depend on their neighbours. They also appear in fixed clusters with a fixed order, and the cluster position depends on the sentence type. The paper implements a rule-based model that generates the right form of each pronoun from its context. It covers obligatory sandhi forms and, in addition, optional ones. The author also compiled a database of test inputs that cover the phenomena, and tested the model against it. The main claim is transparency: each generated form can be traced to the rule that produced it. The author notes that the resources were built by hand and may contain errors, and that the approach can be adapted to other constraint-based frameworks.

## Ideas

- I1. A phenomenon-based test suite as a gate. Compile test inputs by phenomenon, here the cluster order and the sandhi forms, and run the exact-match check before and after each change. This is the same idea as the paper's database, applied to the translator's function words.
- I2. Make every surface choice carry its rule. Add the id of the rule that fired to the output of `en/src/morph.rs`, so that each form can be explained. This follows the transparency goal of the paper and fits Mova's explain requirement.
- I3. Context-conditioned forms. Store the function-word forms of the target language by neighbour, in the same way the encoder of `profile.rs` falls back from concept plus tag plus neighbours to concept alone. A form that depends on the neighbour is then a table entry, not a special case.

## For Mova

Romanian is not a Mova language, so only the method carries over. The rules are applied in a fixed order, which fits the stack of `tools/translate`. The fit is `en/src/morph.rs` (rule ids), the test-suite gate, and the context-conditioned table of the encoder.

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.

```
@inproceedings{gerstenberger2025rule,
  title = {{Rule-based Surface Realization of Romanian Weak Pronouns}},
  author = {Gerstenberger, Ciprian},
  booktitle = {Proceedings of the 9th Workshop on Constraint Grammar and Finite State NLP},
  year = {2025},
  url = {https://aclanthology.org/2025.cgmta-1.2/}
}
```

- [← previous KoBE: Knowledge-Based Machine Translation Evaluation](https://md.mova.elamur.ai/free/en/docs/papers/gekhman-2020-kobe-knowledge-based-machine-translation/)
- [next → Towards Heterogeneous Automatic MT Error Analysis](https://md.mova.elamur.ai/free/en/docs/papers/gimenez-2008-heterogeneous-automatic-mt-error-analysis/)
- [↑ back to Machine translation](https://md.mova.elamur.ai/free/en/docs/papers/mtrans/)

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22 references, 0 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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