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# Automatic Construction of Aramaic-Hebrew Translation Lexicon

**Authors:** [Chaya Liebeskind](https://md.mova.elamur.ai/free/en/docs/papers/authors/chaya-liebeskind/); [Shmuel Liebeskind](https://md.mova.elamur.ai/free/en/docs/papers/authors/shmuel-liebeskind/) · **Year:** 2020 · **Venue:** Proceedings of LT4HALA 2020 - 1st Workshop on Language Technologies for Historical and Ancient Languages **Link:** [aclanthology.org/2020.lt4hala-1.2](https://aclanthology.org/2020.lt4hala-1.2/) · library `aclbulk-2020-liebeskind-automatic-construction-aramaic-hebrew-translation` · **Licence:** [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) (ELRA, LREC proceedings) — summary only

[**0** citations](https://openalex.org/works?filter=cites:W3088821710) openalex-snapshot · 2026-10-14[Proceedings of LT4HALA 2020 - 1st Workshop on Language Technologies for Historical and Ancient Languages](https://aclanthology.org/volumes/2020.lt4hala-1/)[licence](https://creativecommons.org/licenses/by-nc/4.0/)

- [Publisher's page](https://aclanthology.org/2020.lt4hala-1.2/)
- [PDF](https://aclanthology.org/2020.lt4hala-1.2.pdf)
- [OpenAlex](https://openalex.org/W3088821710)

**Authors (2)**

1. [Chaya Liebeskind](https://openalex.org/A5048937508) [ORCID](https://orcid.org/0000-0003-0476-3796) · [Semantic Scholar](https://www.semanticscholar.org/author/2601200) · h 10 · 325 citations · 113 works
2. [Shmuel Liebeskind](https://openalex.org/A5011215522) [ORCID](https://orcid.org/0009-0006-3205-7038) · [Semantic Scholar](https://www.semanticscholar.org/author/73770260) · h 6 · 78 citations · 12 works

Citations and author metrics from openalex-snapshot (2026-10-14); authors with the same name are not always told apart.

## What it is about

The authors build an Aramaic-Hebrew translation lexicon from the parallel Targum Onkelos and Targum Jonathan (Aramaic translations of the Pentateuch and the Prophets, set beside the Hebrew). An IBM model 4 alignment (GIZA++) gives an initial lexicon of 29,335 source terms. For each term, the candidate translations are clustered by string similarity, and a candidate is kept only when its cluster, or a cluster of similar terms, supports it. Five string measures are tested (Levenshtein, Hamming, Jaccard, Jaro and a word-level match on the rarest letters) for three pair types: Hebrew-Hebrew, Aramaic-Aramaic and Aramaic-Hebrew. On 108 sampled source terms (287 annotated pairs) the filtered lexicon reaches F1 0.93 and accuracy 0.89, against 0.88 and 0.79 for the unfiltered IBM output, and 0.82 and 0.70 for a filter on the alignment probability. Jaro similarity with thresholds 0.67, 0.82 and 0.78 works best for the three pair types.

## Ideas

- I1. Jaro similarity with the paper's thresholds (0.67 Hebrew-Hebrew, 0.82 Aramaic-Aramaic, 0.78 Aramaic-Hebrew) as a deterministic filter for candidate gloss pairs. Test it in [The lexicon of Biblical Aramaic](https://md.mova.elamur.ai/free/en/docs/languages/arc/lexicon/) on the Onkelos gloss pairs, against a hand-checked sample.
- I2. The word-level measure: represent each word by its two rarest letters, in order, after dropping prefixes and matres lectionis, and require an exact match. This links Aramaic spelling variants to one lemma in [The lexicon of Biblical Aramaic](https://md.mova.elamur.ai/free/en/docs/languages/arc/lexicon/).
- I3. The paper's error analysis is a ready regression list: 34% of its wrong rejections were single-form words, and 66% came from low similarity scores on pairs such as variant forms of one verb. Keep these as cases that any new filter must not lose.

## For Mova

I1 and I2 go into [The lexicon of Biblical Aramaic](https://md.mova.elamur.ai/free/en/docs/languages/arc/lexicon/). I1 and I3 go into `languages/arc-x-targum/` as a test on Targum glosses. Nothing is built from the data; the pairs are used only for measurement, since the licence is non-commercial.

## Cite

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

```
@inproceedings{liebeskind2020automatic,
  title = {{Automatic Construction of Aramaic-Hebrew Translation Lexicon}},
  author = {Liebeskind, Chaya and Liebeskind, Shmuel},
  booktitle = {Proceedings of LT4HALA 2020 - 1st Workshop on Language Technologies for Historical and Ancient Languages},
  year = {2020},
  url = {https://aclanthology.org/2020.lt4hala-1.2/}
}
```

- [← previous Lemmatization and POS-tagging process by using joint learning approach. Experimental results on Classical Armenian, Old Georgian, and Syriac](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2020-gorene-lemmatization-pos-tagging-process-joint/)
- [next → A Transformer-based parser for Syriac morphology](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2023-naaijer-transformer-based-parser-syriac-morphology/)
- [↑ back to Aramaic](https://md.mova.elamur.ai/free/en/docs/papers/arc/)

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