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# Handling Stress in Finite-State Morphological Analyzers for Ancient Greek and Ancient Hebrew

**Authors:** [Daniel G. Swanson](https://md.mova.elamur.ai/free/en/docs/papers/authors/daniel-g-swanson/); [Francis M. Tyers](https://md.mova.elamur.ai/free/en/docs/papers/authors/francis-m-tyers/) · **Year:** 2022 · **Venue:** Proceedings of the Second Workshop on Language Technologies for Historical and Ancient Languages **Link:** [aclanthology.org/2022.lt4hala-1.15](https://aclanthology.org/2022.lt4hala-1.15/) · library `aclbulk-2022-swanson-handling-stress-finite-state-morphological` · **Licence:** [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) — summary only

[**2** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/aclbulk-2022-swanson-handling-stress-finite-state-morphological/) of the 140673 papers whose bibliographies we read[Proceedings of the Second Workshop on Language Technologies for Historical and Ancient Languages](https://aclanthology.org/volumes/2022.lt4hala-1/)[licence](https://creativecommons.org/licenses/by-nc/4.0/)

- [Publisher's page](https://aclanthology.org/2022.lt4hala-1.15/)
- [PDF](https://aclanthology.org/2022.lt4hala-1.15.pdf)

**Authors (2)**

1. Daniel G. Swanson
2. Francis M. Tyers

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

## What it is about

The authors argue that finite-state analysers can model lexical stress if the lexicon carries control characters beyond the surface form. They build two Apertium-based prototypes with the lexd compiler and two-level rules: Ancient Greek, with full accent placement, and Ancient Hebrew, with stress movement for the vav-consecutive forms, which move the stress to the penultimate syllable. Analysis coverage is 95.2% of tokens in the Greek New Testament (146,265 of 153,665) and 64.2% of tokens in Hebrew Genesis (13,201 of 20,573). Both analysers overgenerate: about 8% of Greek words, and in Hebrew some pronominal forms. Nominal morphology in the Hebrew analyser is incomplete.

## Ideas

- I1. Describe the Hebrew verb system with interlaced lexical entries (a root, with slots for each stem pattern) instead of listing forms; the same root table can serve the weak verbs in [The weak verbs](https://md.mova.elamur.ai/free/en/docs/languages/hbo/07-weak-verbs/).
- I2. Carry stress as a feature on the verb: a vav-consecutive form gets a stress-moved flag that derives the penultimate vowel and the deleted final syllable. Mova derives these forms rather than storing them.
- I3. Use the paper's per-book coverage (Genesis 64.2%) as the first yardstick for the `tools/hbo` lexicon: report coverage per book, and treat any drop as a regression.
- I4. Test the overgeneration rate on a held-out book with a fixed list of known-wrong forms, the same way they report it.

## For Mova

I1 and I2 apply to [The verb](https://md.mova.elamur.ai/free/en/docs/languages/hbo/06-verb/) and `07-weak-verbs.md`; I3 is a measure for `tools/hbo` and `macula`; I4 is a test for the same. The paper is licensed non-commercial, so we use only the summary and do not carry its code or tables into a release.

## Cite

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

```
@inproceedings{swanson2022handling,
  title = {{Handling Stress in Finite-State Morphological Analyzers for Ancient Greek and Ancient Hebrew}},
  author = {Swanson, Daniel G. and Tyers, Francis M.},
  booktitle = {Proceedings of the Second Workshop on Language Technologies for Historical and Ancient Languages},
  year = {2022},
  url = {https://aclanthology.org/2022.lt4hala-1.15/}
}
```

- [← previous Word Sense Induction with Attentive Context Clustering](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2021-stekel-word-sense-induction-attentive-context/)
- [next → Style Classification of Rabbinic Literature for Detection of Lost Midrash Tanhuma Material](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2022-tannor-style-classification-rabbinic-literature-detection/)
- [↑ back to Ancient Hebrew](https://md.mova.elamur.ai/free/en/docs/papers/hbo/)

## References

13 references, 1 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Crane, G. (1991). Generating and Parsing Classical Greek. Literary and Linguistic Computing, 6(4):243–245, 01. [↗](https://doi.org/10.1093/llc/6.4.243)
2. Forcada, M. L., Ginestı́-Rosell, M., Nordfalk, J., O’Regan, J., Ortiz-Rojas, S., Pérez-Ortiz, J. A., Sánchez-Martı́nez, F., Ramı́rez-Sánchez, G., and Tyers, F. M. (2011). Apertium: a free/open-source platform for rule-based machine translation. Machine translation, 25(2):127–144. [↗](https://doi.org/10.1007/s10590-011-9090-0)
3. Gesenius, W. and Kautzsch, E. (2006). Gesenius’ Hebrew Grammar. Dover Publications. [find](https://scholar.google.com/scholar?q=Gesenius%2C+W%2E+and+Kautzsch%2C+E%2E+%282006%29%2E+Gesenius%E2%80%99+Hebrew+Grammar%2E+Dover+Publications%2E)
4. Karttunen, L. (1991). Finite-state constraints. In Proceedings of the International Conference on Current Issues in Computational Linguistics. [find](https://scholar.google.com/scholar?q=Karttunen%2C+L%2E+%281991%29%2E+Finite%2Dstate+constraints%2E+In+Proceedings+of+the+International+Conference+on+Current+Issues+in+Computational+Linguistics%2E)
5. Khanna, T., Washington, J., Tyers, F., Bayatlı, S., Swanson, D., Pirinen, T., Tang, I., and Alòs i Font, H. (2021). Recent advances in apertium, a free / open-source rule-based machine translation platform for low-resource languages. Machine Translation. [↗](https://doi.org/10.1007/s10590-021-09260-6)
6. Koskenniemi, K. (1983). Two-level Morphology: A General Computational Model for Word-Form Recognition and Production. phdthesis. [find](https://scholar.google.com/scholar?q=Koskenniemi%2C+K%2E+%281983%29%2E+Two%2Dlevel+Morphology%3A+A+General+Computational+Model+for+Word%2DForm+Recognition+and+Production%2E+phdthesis%2E)
7. Lindén, K., Silfverberg, M., and Pirinen, T. (2009). Hfst tools for morphology–an efficient open-source package for construction of morphological analyzers. In International Workshop on Systems and Frameworks for Computational Morphology, pages 28–47. Springer. [find](https://scholar.google.com/scholar?q=Linde%CC%81n%2C+K%2E%2C+Silfverberg%2C+M%2E%2C+and+Pirinen%2C+T%2E+%282009%29%2E+Hfst+tools+for+morphology%E2%80%93an+efficient+open%2Dsource+package+for+construction+of+morphological+analyzers%2E+In+International+Workshop+on+Systems+and+F)
8. Packard, D. W. (1973). Computer-assisted morphological analysis of Ancient Greek. In COLING 1973 Volume 2: Computational And Mathematical Linguistics: Proceedings of the International Conference on Computational Linguistics. [find](https://scholar.google.com/scholar?q=Packard%2C+D%2E+W%2E+%281973%29%2E+Computer%2Dassisted+morphological+analysis+of+Ancient+Greek%2E+In+COLING+1973+Volume+2%3A+Computational+And+Mathematical+Linguistics%3A+Proceedings+of+the+International+Conference+on+Co)
9. Smith, N. (2016). Morphological analysis of historical languages. Bulletin of the Institute of Classical Studies, 59(2):89–102. [↗](https://doi.org/10.1111/j.2041-5370.2016.12040.x)
10. Swanson, D. and Howell, N. (2021). Lexd: A finite-state lexicon compiler for non-suffixational morphologies. In Mika Hämäläinen, et al., editors, Multilingual Facilitation. University of Helsinki Library. [↗](https://doi.org/10.31885/9789515150257.13)
11. van Emde Boas, E., Rijksbaron, A., Huitink, L., and de Bakker, M. (2019). The Cambridge Grammar of Classical Greek. Cambridge University Press. [↗](https://doi.org/10.1017/9781139027052)
12. Wintner, S. (2008). Strengths and weaknesses of finite-state technology: a case study in morphological grammar development. 14(4):457–469. [↗](https://doi.org/10.1017/s1351324907004676)
13. Yona, S. and Wintner, S. (2008). A finite-state morphological grammar of hebrew. 14(2):173–190. [↗](https://doi.org/10.1017/s1351324906004384) [our card](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2005-yona-finite-state-morphological-grammar-hebrew/)