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# How Much Does Lookahead Matter for Disambiguation? Partial Arabic Diacritization Case Study

**Authors:** Saeed Esmail; [Kfir Bar](https://md.mova.elamur.ai/free/en/docs/papers/authors/kfir-bar/); [Nachum Dershowitz](https://md.mova.elamur.ai/free/en/docs/papers/authors/nachum-dershowitz/) · **Year:** 2022 · **Venue:** Computational Linguistics **Link:** [aclanthology.org/2022.cl-4.20](https://aclanthology.org/2022.cl-4.20/) · library `cl-2022-esmail-how-much-does-lookahead-matter` · **Licence:** [CC BY-NC-ND 4.0](https://creativecommons.org/licenses/by-nc-nd/4.0/) — summary only

[**7** citations](https://openalex.org/works?filter=cites:W4292850852) openalex · 2026-10-18[**3** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/cl-2022-esmail-how-much-does-lookahead-matter/) of the 140673 papers whose bibliographies we read[Computational Linguistics](https://aclanthology.org/volumes/2022.cl-4/)[licence](https://creativecommons.org/licenses/by-nc-nd/4.0/)

- [Publisher's page](https://aclanthology.org/2022.cl-4.20/)
- [PDF](https://aclanthology.org/2022.cl-4.20.pdf)
- [DOI 10.1162/coli_a_00456](https://doi.org/10.1162/coli_a_00456)
- [OpenAlex](https://openalex.org/W4292850852)

**Authors (3)**

1. [Saeed Esmail](https://openalex.org/A5083218904) [Semantic Scholar](https://www.semanticscholar.org/author/2182639122) · h 1 · 7 citations · 2 works
2. [Kfir Bar](https://openalex.org/A5069195550) [ORCID](https://orcid.org/0000-0002-1354-2955) · [Semantic Scholar](https://www.semanticscholar.org/author/50143541) · h 11 · 362 citations · 81 works
3. [Nachum Dershowitz](https://openalex.org/A5039993352) [ORCID](https://orcid.org/0000-0003-0363-2735) · [Semantic Scholar](https://www.semanticscholar.org/author/1759551) · h 43 · 9037 citations · 540 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 authors ask which short vowels a reader of unpointed Arabic really needs, and they print only those. Two neural diacritizers are trained on the Tashkeela corpus: a unidirectional LSTM that sees only the words already read, and a transformer that sees the whole sentence. Where the two disagree, the whole-sentence reading is kept and its diacritic is printed; everywhere else the letter stays bare. A new set of 75 MSA tweets, fully and partially vowelized by native readers (who kept 19–26% of the diacritics), supports the evaluation. The partial diacritizer improves downstream translation over no diacritics and over random selection. The full-sentence model reaches 3.57 DER / 8.52 WER with case endings on the Tashkeela test set, including NO DIACRITIC.

## Ideas

- I1. Lookahead as disagreement: run a left-context-only analysis and a full-sentence analysis over the same text, and mark each word where they differ as "needs lookahead". This is a deterministic diff of two passes, and it names the words a left-to-right reader cannot settle.
- I2. Measure the lookahead set on unpointed Biblical Hebrew: how many MACULA tokens change segmentation or lemma when the right context is removed. It gives a number for how much unpointed text really depends on what follows.
- I3. Data rule for training gold: drop lines whose share of marked letters falls under a threshold (the paper uses 50% for MSA against 80% in earlier work). Keep the threshold as a recorded parameter, so every run can state it.

## For Mova

I1 and I2 go into `tools/hbo` (unpointed mode), as a second pass next to the segmenter; the lookahead set is also a check in [13. Biblical Hebrew in Mova: the tools](https://md.mova.elamur.ai/free/en/docs/languages/hbo/13-mova-tools/). I2 uses `treebanks/hbo/ptnk` as its gold. I3 is a rule for any pointed training text built for vowel restoration in `tools/hbo`.

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.1162/coli_a_00456](https://doi.org/10.1162/coli_a_00456)

```
@article{esmail2022how,
  title = {{How Much Does Lookahead Matter for Disambiguation? Partial Arabic Diacritization Case Study}},
  author = {Esmail, Saeed and Bar, Kfir and Dershowitz, Nachum},
  journal = {Computational Linguistics},
  year = {2022},
  doi = {10.1162/coli\_a\_00456},
  url = {https://doi.org/10.1162/coli_a_00456}
}
```

- [← previous Dependency Parsing of Modern Standard Arabic with Lexical and Inflectional Features](https://md.mova.elamur.ai/free/en/docs/papers/cl-2013-marton-dependency-parsing-modern-standard-arabic/)
- [next → Arabic Diacritization Using Morphologically Informed Character-Level Model](https://md.mova.elamur.ai/free/en/docs/papers/coling-2024-elmallah-arabic-diacritization-morphologically-informed-character/)
- [↑ back to Semitic languages](https://md.mova.elamur.ai/free/en/docs/papers/sem/)

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