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# Identifying Broken Plurals in Unvowelised Arabic Text

**Authors:** Abduelbaset Goweder; [Massimo Poesio](https://md.mova.elamur.ai/free/en/docs/papers/authors/massimo-poesio/); Anne De Roeck; Jeff Reynolds · **Year:** 2004 · **Venue:** Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing **Link:** [aclanthology.org/W04-3232](https://aclanthology.org/W04-3232/) · library `aclbulk-2004-goweder-identifying-broken-plurals-unvowelised-arabic` · **Licence:** [CC BY-NC-SA 3.0](https://creativecommons.org/licenses/by-nc-sa/3.0/) (ACL Anthology, before 2016) — summary only

[**18** citations](https://openalex.org/works?filter=cites:W1519890653) openalex · 2026-10-19[Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing](https://aclanthology.org/volumes/W04-32/)[licence](https://creativecommons.org/licenses/by-nc-sa/3.0/)

- [Publisher's page](https://aclanthology.org/W04-3232/)
- [PDF](https://aclanthology.org/W04-3232.pdf)
- [OpenAlex](https://openalex.org/W1519890653)

**Authors (4)**

1. [Abduelbaset Goweder](https://openalex.org/A5059580619) [Semantic Scholar](https://www.semanticscholar.org/author/2255848) · h 3 · 42 citations · 16 works
2. [Massimo Poesio](https://openalex.org/A5047065550) [ORCID](https://orcid.org/0000-0001-8469-2072) · [Semantic Scholar](https://www.semanticscholar.org/author/1678591) · h 47 · 10176 citations · 588 works
3. [Anne De Roeck](https://openalex.org/A5109882660) [Semantic Scholar](https://www.semanticscholar.org/author/2023598) · h 21 · 3377 citations · 139 works
4. [Jeff Reynolds](https://openalex.org/A5072577847) [Semantic Scholar](https://www.semanticscholar.org/author/2068158776) · h 3 · 442 citations · 12 works

Citations and author metrics from openalex (2026-10-19); authors with the same name are not always told apart.

## What it is about

Broken plurals (formed by changing the consonant pattern of the singular, not by adding a suffix) cannot be undone by affix stripping, so a light stemmer leaves them as separate stems. The authors compare four ways of detecting them in unvowelised text. The first is simple matching of 39 grammar-book patterns after light stemming, which gives high recall (99.5%) and low precision (13.8%) on data set 2. The second restricts the pattern letters by hand, which lifts precision to about 50%. The third is a decision tree (C4.5) per pattern. The fourth is a dictionary of about 3,580 broken-plural stems, built from an 18.5-million-word corpus and checked by a linguist. The dictionary gives precision 86.9% and F 92.5 on data set 2, and with affix refinement 92.3% and F 96.0. A light stemmer with broken-plural recognition, indexing "stem + BP", beats full-word, root and basic-stem indexing in a 50-query retrieval test (p < .01).

## Ideas

- I1. A table of restricted templates with exceptions: write each broken-plural pattern as fixed letters plus a set of allowed letters in the meta-letter slots, and a short list of known exceptions (the paper's verbal nominalisations with a t-infix). It is rule-based, readable, and can be measured on its own. Candidate place: the noun-class tables in [The Noun, the Adjective and the Numeral](https://md.mova.elamur.ai/free/en/docs/languages/hbo/04-noun/), and the plural classes in [The noun in Biblical Aramaic](https://md.mova.elamur.ai/free/en/docs/languages/arc/nouns/).
- I2. A bootstrapped lexicon: run a cheap, high-recall rule over a large corpus, hand-correct the output once, and keep the corrected list as a lookup table. The paper's 3,580-stem list shows the cost is small once the cheap rule exists. For Mova, the same step can build lemma lists from the MACULA-derived lexicon in `tools/macula dict`.
- I3. A retrieval measure: a 50-query test with relevance judgments, comparing full word, root and lemma indexes, as the paper does. Mova has no search test of this kind yet; it would measure whether lemma conflation helps before any stemmer is built.

## For Mova

I1 is a candidate test for the noun chapters: [The Noun, the Adjective and the Numeral](https://md.mova.elamur.ai/free/en/docs/languages/hbo/04-noun/) for Ancient Hebrew plural classes, and [The noun in Biblical Aramaic](https://md.mova.elamur.ai/free/en/docs/languages/arc/nouns/) for Aramaic. I2 uses `tools/macula dict` as the seed. I3 is a measure, not a rule; it is only worth running if Mova gets a retrieval component. Arabic itself is not a Mova language yet.

## Cite

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

```
@inproceedings{goweder2004identifying,
  title = {{Identifying Broken Plurals in Unvowelised Arabic Text}},
  author = {Goweder, Abduelbaset and Poesio, Massimo and Roeck, Anne De and Reynolds, Jeff},
  booktitle = {Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing},
  year = {2004},
  url = {https://aclanthology.org/W04-3232/}
}
```

- [← previous Issues in Arabic Orthography and Morphology Analysis](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2004-buckwalter-issues-arabic-orthography-morphology-analysis/)
- [next → Arabic Tokenization, Part-of-Speech Tagging and Morphological Disambiguation in One Fell Swoop](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2005-habash-arabic-tokenization-part-speech-tagging/)
- [↑ back to Semitic languages](https://md.mova.elamur.ai/free/en/docs/papers/sem/)

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