[Mova](https://md.mova.elamur.ai/free/en/) · [this page in HTML](https://mova.elamur.ai/free/en/docs/papers/nirenburg-1986-knowledge-based-machine-translation/) [home](https://md.mova.elamur.ai/free/en/) / [docs](https://md.mova.elamur.ai/free/en/docs/) / [papers](https://md.mova.elamur.ai/free/en/docs/papers/) / [Machine translation](https://md.mova.elamur.ai/free/en/docs/papers/mtrans/) / On Knowledge-Based Machine Translation # On Knowledge-Based Machine Translation **Authors:** [Sergei Nirenburg](https://md.mova.elamur.ai/free/en/docs/papers/authors/sergei-nirenburg/), Victor Raskin, Allen Tucker · **Year:** 1986 · **Venue:** Coling 1986, Volume 1: The 11th International Conference on Computational Linguistics **Link:** [aclanthology.org/C86-1148](https://aclanthology.org/C86-1148/) · **Licence:** [CC BY-NC-SA 3.0](https://creativecommons.org/licenses/by-nc-sa/3.0/) — summary only [**3** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/nirenburg-1986-knowledge-based-machine-translation/) of the 140673 papers whose bibliographies we read[Coling 1986 Volume 1: The 11th International Conference on Computational Linguistics](https://aclanthology.org/volumes/C86-1/)[licence](https://creativecommons.org/licenses/by-nc-sa/3.0/) - [Publisher's page](https://aclanthology.org/C86-1148/) - [PDF](https://aclanthology.org/C86-1148.pdf) **Authors (3)** 1. Sergei Nirenburg 2. Victor Raskin 3. Allen Tucker Citations and author metrics from OpenAlex (); authors with the same name are not always told apart. ## What it is about The paper describes the interlingua of the TRANSLATOR project, which is meant to represent the meaning of texts in a limited subworld. The interlingua has two parts. DIL, the dictionary of the interlingua, describes the concepts and their semantics for the subworld. TIL, the text of the interlingua, holds the instances that a given text produces. Because the interlingua is an artificial language, its syntax and semantics can be controlled. The authors answer four common objections to knowledge-based MT: that full meaning is unnecessary, that translation can start before parsing ends, that syntax can be ignored, and that generation is simple. They reject each, with arguments but no measurements. The work is a design specification; the implementation is future work. ## Ideas - I1. Keep the concept dictionary and the instances in two tables. The meta-world concepts (in `meta.rs`) should not change with each verse, while the instances for one verse are rebuilt. Count how many concept entries change between runs; that count should be near zero. - I2. Make the generation choice a counted decision. The paper says generation needs real choices. In the encoder, measure how often the chosen target chunk matches the author's own word against the most frequent chunk, which is the control. - I3. Define a subworld and count it. Measure how many distinct concepts a book or a genre needs, and how the count grows with each added text. This gives a concrete measure of the subworld the translator covers. ## For Mova The distinction between dictionary and text fits the meta-world, where `meta.rs` holds the concepts and the reader builds the instances. The objections are useful as a checklist for the design, though they are argued, not tested. The first concrete step is the count of concept changes between two identical runs, which tests the stability claim. 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{nirenburg1986knowledge, title = {{On Knowledge-Based Machine Translation}}, author = {Nirenburg, Sergei and Raskin, Victor and Tucker, Allen}, booktitle = {Coling 1986 Volume 1: The 11th International Conference on Computational Linguistics}, year = {1986}, url = {https://aclanthology.org/C86-1148/} } ``` - [← previous Expanding the JHU Bible Corpus for Machine Translation of the Indigenous Languages of North America](https://md.mova.elamur.ai/free/en/docs/papers/nicolai-2021-expanding-jhu-bible-corpus-machine/) - [next → KBMT-89 - A knowledge-based MT project at Carnegie Mellon University](https://md.mova.elamur.ai/free/en/docs/papers/nirenburg-1989-kbmt-89-knowledge-based-mt/) - [↑ back to Machine translation](https://md.mova.elamur.ai/free/en/docs/papers/mtrans/) ## References 4 references, 0 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet. 1. Brachman, R. and J. Schmoltze 1985. An overview on the KL-ONE knowledge representation system. Cognitive Science, vol. 9, issue 2. [find](https://scholar.google.com/scholar?q=Brachman%2C+R%2E+and+J%2E+Schmoltze+1985%2E+An+overview+on+the+KL%2DONE+knowledge+representation+system%2E+Cognitive+Science%2C+vol%2E+9%2C+issue+2%2E) 2. Carbonell, J. and M. Tomita 1985. New approaches to machine translation. In: S. Nirenburg (ed.). [find](https://scholar.google.com/scholar?q=Carbonell%2C+J%2E+and+M%2E+Tomita+1985%2E+New+approaches+to+machine+translation%2E+In%3A+S%2E+Nirenburg+%28ed%2E%29%2E) 3. Johnson, R. and P. Whitelock 1985. Machine translation as an expert task. In: S. Nirenburg (ed.). Nirenburg, S. (ed.), Proceedings of the Conference on Theoretical and Methodological Issues in Machine Translation. [find](https://scholar.google.com/scholar?q=Johnson%2C+R%2E+and+P%2E+Whitelock+1985%2E+Machine+translation+as+an+expert+task%2E+In%3A+S%2E+Nirenburg+%28ed%2E%29%2E+Nirenburg%2C+S%2E+%28ed%2E%29%2C+Proceedings+of+the+Conference+on+Theoretical+and+Methodological+Issues+in+Machine) 4. Hamilton, NY, August 1985. [find](https://scholar.google.com/scholar?q=Hamilton%2C+NY%2C+August+1985%2E)