---
title: "Impact de l'agglutination dans l'extraction de termes en arabe"
description: "The paper tackles term extraction for Modern Standard Arabic. 21 references. Among them: 0."
authors: ["Wafa Neifar", "Thierry Hamon", "Pierre Zweigenbaum", "Mariem Ellouze", "Lamia Hadrich Belguith"]
year: 2016
venue: "Actes de la conférence conjointe JEP-TALN-RECITAL 2016. volume 2 : TALN (Posters)"
source: "https://aclanthology.org/2016.jeptalnrecital-poster.20/"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/neifar-2016-impact-de-l-agglutination-dans/"
---
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# Impact de l'agglutination dans l'extraction de termes en arabe standard moderne (Adaptation of a term extractor to the Modern Standard Arabic language)

**Authors:** Wafa Neifar, Thierry Hamon, [Pierre Zweigenbaum](https://md.research.elamur.ai/free/en/authors/pierre-zweigenbaum/), [Mariem Ellouze](https://md.research.elamur.ai/free/en/authors/mariem-ellouze/) and [Lamia Hadrich Belguith](https://md.research.elamur.ai/free/en/authors/lamia-hadrich-belguith/) · **Year:** 2016 · **Venue:** [Actes de la conférence conjointe JEP-TALN-RECITAL 2016. volume 2 : TALN (Posters)](https://md.research.elamur.ai/free/en/venues/jeptalnrecital/) ([JEP-TALN-RECITAL (the French-speaking conferences on speech and natural language processing) 2016](https://md.research.elamur.ai/free/en/venues/jeptalnrecital/2016/)) · **Publisher:** [AFCP - ATALA](https://md.research.elamur.ai/free/en/publishers/afcp-atala/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2016.jeptalnrecital-poster.20/) · [PDF](https://aclanthology.org/2016.jeptalnrecital-poster.20.pdf) · [OpenAlex](https://openalex.org/W3088690919)

**Citations:** 0 citations (OpenAlex, 2026-10-14)

## Summary
The paper tackles term extraction for Modern Standard Arabic. Earlier Arabic systems were poorly documented, not publicly available, and evaluated only on top-ranked terms. The authors port the open-source extractor YATEA, originally built for French and English, to MSA. They rely on MADA+TOKAN for morphological analysis, vowelled lemmas, clitic segmentation, and case and state features.

The adaptation covers YATEA's first two stages: splitting text at syntactic boundaries into maximal noun phrases, then parsing those phrases into head/modifier structures with recursive patterns. Arabic-specific additions include extra boundary items (pseudo-verbs, adverbs, fixed expressions, proclitic-based breaks), and patterns that use gender, number, case and the construct state (al-iḍāfah). Enclitics are left for later.

On a medical corpus of 15,532 words, handling proclitics raises the precision of maximal complex candidates from 65.7% to 72.1% and reduces the number of candidates. The work matters because it gives a reproducible, linguistically grounded baseline for Arabic terminology extraction.

## Key points
- The base tool is YATEA, a freely available Perl extractor with three stages: boundary segmentation, pattern-based head/modifier parsing, and statistical ranking (e.g. C-Value). Only the first two stages were adapted.
- Preprocessing uses MADA+TOKAN, which supplies vowelled lemmas, clitic decomposition, and case/state marks. These features reduce the damage caused by ambiguous unvowelled forms.
- Of 400 maximal candidate terms judged manually on medical texts, 288 were domain-correct (72.1%). Without proclitic handling, precision was 65.7%.
- Remaining errors come from POS tagging mistakes, missing vowels, and the difficulty of handling agglutination. Enclitics are not yet treated.
- Prepositions that MADA+TOKAN wrongly tags as nouns (e.g. "from", "to", "between") are explicitly forbidden at the start or end of a term.

## Interesting ideas
- Instead of requiring the tagger to be correct, the authors add a list of tags and words that may never open or close a term, which absorbs a known systematic tagger error.
- Morphological case and construct-state marks serve as direct evidence for which noun is the head and which is the modifier in a nominal group.
- The paper finds candidate phrases by cutting text at "negative" boundaries (conjugated verbs, pronouns, punctuation, some adverbs and fixed expressions), so maximal noun groups emerge without a full parse.
- Clitic segmentation is turned on only where it is reliable (proclitics) and deferred where it is error-prone (enclitics), and the gain is measured against the unsegmented baseline.
- The authors criticise evaluating only top-ranked candidates and instead check a larger sample of maximal candidates, because any method looks good at the top of its ranking.

## For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

- **I1** (tokens): Known recurring tagger confusions could be listed as explicit, explainable edge constraints on chunks, rather than retraining the tagger every time.
- **I2** (tree): English genitive "'s" and "of"-phrases could feed the parser and its repair rules as explicit, traceable head/modifier cues inside noun compounds.
- **I3** (world): A cheap boundary-based chunker could propose domain entity and term candidates for the knowledge layer, and each candidate stays explainable through the boundaries that delimit it.
- **I4** (learn): When adding a preprocessing step, roll it out piecemeal and keep a with/without ablation as a control, so the effect of each step on precision is visible.
- **I5** (learn): Mova's evaluations should sample beyond the most confident outputs, so that strong head-of-list results do not hide weak tails.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

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## Cite

Cite as: Wafa Neifar, Thierry Hamon, Pierre Zweigenbaum, Mariem Ellouze and Lamia Hadrich Belguith. 2016. Impact de l'agglutination dans l'extraction de termes en arabe standard moderne (Adaptation of a term extractor to the Modern Standard Arabic language). Actes de la conférence conjointe JEP-TALN-RECITAL 2016. volume 2 : TALN (Posters).

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

```bibtex
@inproceedings{neifar2016impact,
  title = {{Impact de l'agglutination dans l'extraction de termes en arabe standard moderne (Adaptation of a term extractor to the Modern Standard Arabic language)}},
  author = {Wafa Neifar, Thierry Hamon, Pierre Zweigenbaum, Mariem Ellouze and Lamia Hadrich Belguith},
  booktitle = {Actes de la conférence conjointe JEP-TALN-RECITAL 2016. volume 2 : TALN (Posters)},
  year = {2016},
  url = {https://aclanthology.org/2016.jeptalnrecital-poster.20/}
}
```

- [← previous Grover Hudson, Northeast African Semitic: Lexical Comparisons and Analysis](https://md.research.elamur.ai/free/en/papers/bausi-2016-grover-hudson-northeast-african-semitic/)
- [next → Interactive Tools and Tasks for the Hebrew Bible: From Language Learning to Textual Criticism](https://md.research.elamur.ai/free/en/papers/winther-nielsen-2016-interactive-tools-tasks-hebrew-bible/)
- [↑ back to papers of 2016](https://md.research.elamur.ai/free/en/papers/2016/page/6/)

## References

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

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*Updated 2 November 2026*