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# The jsRealB Text Realizer: Organization and Use Cases -- Revised version

**Authors:** [Guy Lapalme](https://md.mova.elamur.ai/free/en/docs/papers/authors/guy-lapalme/) · **Year:** 2020 · **Venue:** arXiv:2012.15425 **Link:** [arxiv.org/abs/2012.15425](https://arxiv.org/abs/2012.15425) · **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)

[**0** citations](https://openalex.org/works?filter=cites:W4287547269) openalex · 2026-10-18[**2** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lapalme-2020-jsrealb-text-realizer-organization-use/) of the 140673 papers whose bibliographies we read[arXiv:2012.15425](https://openalex.org/S4306400194)[licence](http://creativecommons.org/licenses/by/4.0/)

- [Publisher's page](https://arxiv.org/abs/2012.15425)
- [PDF](https://arxiv.org/pdf/2012.15425)
- [arXiv 2012.15425](https://arxiv.org/abs/2012.15425)
- [OpenAlex](https://openalex.org/W4287547269)

**Authors (1)**

1. [Guy Lapalme](https://openalex.org/A5004268705) h 30 · 10081 citations · 305 works

Citations and author metrics from openalex (2026-10-18); authors with the same name are not always told apart.

## What it is about

The paper describes the design of jsRealB, a text realiser for English and French that runs in a web page or as a Node module. Its input is a specification inspired by constituent syntax, with a dependency-style notation also available. The realiser takes care of agreement, conjugation, elision and word order, and it can build negative, passive and interrogative forms from one affirmative specification. The author shows that producing well-formed text is harder than it looks, because each language has its own details. The system has been used for data-to-text applications, for rebuilding literary sentences from Universal Dependency annotations, and in a Python port. The paper is a design report, and it gives many small examples of the rules at work.

## Ideas

- I1. Variants as tree transformations. Derive the negative, passive and interrogative forms of an English tree by ordered transformations in `en/src/lin.rs`, and check on English UD sentences that each variant maps back to the original tree. A failed round trip is a counted error.
- I2. Use UD reproduction as an exact-mode test. The paper rebuilds sentences from UD annotations. For the English dev data, rebuild each sentence from its tree and count exact matches per class (word order, agreement, punctuation). This gives the residual of the surface step in bits.
- I3. Keep agreement and elision in separate, ordered rule tables in `en/src/morph.rs`, each built from counts and kept in `BTreeMap` order. For the translator's target side, the same split gives the function-word rules that open problem 4 needs.

## For Mova

The paper fits `en/src/lin.rs` and `en/src/morph.rs`, the English realisation side. The variant-by-transformation idea and the round-trip test on UD sentences are the parts to borrow. French is outside the current scope, so only the design of the rule tables carries over.

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. [arXiv 2012.15425](https://arxiv.org/abs/2012.15425)

```
@misc{lapalme2020jsrealb,
  title = {{The jsRealB Text Realizer: Organization and Use Cases -- Revised version}},
  author = {Lapalme, Guy},
  year = {2020},
  eprint = {2012.15425},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2012.15425}
}
```

- [← previous The Rosetta project](https://md.mova.elamur.ai/free/en/docs/papers/landsbergen-1989-rosetta-project/)
- [next → GenDR: A Generic Deep Realizer with Complex Lexicalization](https://md.mova.elamur.ai/free/en/docs/papers/lareau-2018-gendr-generic-deep-realizer-complex/)
- [↑ back to Machine translation](https://md.mova.elamur.ai/free/en/docs/papers/mtrans/)

## References

23 references, 5 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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8. Marie-Catherine de Marneffe, Christopher D. Manning, Joakim Nivre, and Daniel Zeman. Universal Dependencies. Computational Linguistics, 47(2):255–308, 07 2021. [find](https://scholar.google.com/scholar?q=Marie%2DCatherine+de+Marneffe%2C+Christopher+D%2E+Manning%2C+Joakim+Nivre%2C+and+Daniel+Zeman%2E+Universal+Dependencies%2E+Computational+Linguistics%2C+47%282%29%3A255%E2%80%93308%2C+07+2021%2E) [our card](https://md.mova.elamur.ai/free/en/docs/papers/demarneffe-2021-universal-dependencies/)
9. Michael Elhadad and Jacques Robin. An overview of SURGE: a reusable comprehensive syntactic realization component. In Eighth International Natural Language Generation Workshop (Posters and Demonstrations), 1996. [find](https://scholar.google.com/scholar?q=Michael+Elhadad+and+Jacques+Robin%2E+An+overview+of+SURGE%3A+a+reusable+comprehensive+syntactic+realization+component%2E+In+Eighth+International+Natural+Language+Generation+Workshop+%28Posters+and+Demonstrati) [our card](https://md.mova.elamur.ai/free/en/docs/papers/elhadad-1996-overview-surge-reusable-comprehensive-syntactic/)
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12. Guy Lapalme. Verbalizing AMR structures. [http://rali.iro.umontreal.ca/rali/](http://rali.iro.umontreal.ca/rali/) sites/default/files/publis/GoPhi.pdf, Aug 2019. [↗](http://rali.iro.umontreal.ca/rali/)
13. Guy Lapalme. Regenerating sentences from Universal Dependencies structures. [http://rali.iro.umontreal.ca/JSrealB/current/demos/UDregenerator/](http://rali.iro.umontreal.ca/JSrealB/current/demos/UDregenerator/) UDregenerator.pdf, Dec 2020. [↗](http://rali.iro.umontreal.ca/JSrealB/current/demos/UDregenerator/)
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