---
title: "Interactive Annotation for Event Modality in Modern Standard and"
description: "Arabic lacked a large corpus labelled for event modality, meaning potential rather than actual events: obligation, permission… 24 references."
authors: ["Rania Al-Sabbagh", "Roxana Girju", "Jana Diesner"]
year: 2014
venue: "Proceedings of LAW VIII - The 8th Linguistic Annotation Workshop"
source: "https://aclanthology.org/W14-4920/"
doi: "10.3115/v1/w14-4920"
licence: "CC BY-NC-SA 3.0 (ACL Anthology, before 2016)"
licence_url: "https://creativecommons.org/licenses/by-nc-sa/3.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/sabbagh-2014-interactive-annotation-event-modality-modern/"
---
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# Interactive Annotation for Event Modality in Modern Standard and Egyptian Arabic Tweets

**Authors:** [Rania Al-Sabbagh](https://md.research.elamur.ai/free/en/authors/rania-al-sabbagh/), [Roxana Girju](https://md.research.elamur.ai/free/en/authors/roxana-girju/) and [Jana Diesner](https://md.research.elamur.ai/free/en/authors/jana-diesner/) · **Year:** 2014 · **Venue:** [Proceedings of LAW VIII - The 8th Linguistic Annotation Workshop](https://md.research.elamur.ai/free/en/venues/law-viii-the-linguistic-annotation-workshop/) ([LAW VIII - The Linguistic Annotation Workshop 2014](https://md.research.elamur.ai/free/en/venues/law-viii-the-linguistic-annotation-workshop/2014/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY-NC-SA 3.0 (ACL Anthology, before 2016)](https://creativecommons.org/licenses/by-nc-sa/3.0/)

**Links:** [Publisher's page](https://aclanthology.org/W14-4920/) · [PDF](https://aclanthology.org/W14-4920.pdf) · [DOI 10.3115/v1/w14-4920](https://doi.org/10.3115/v1/w14-4920) · [OpenAlex](https://openalex.org/W2251716009)

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

## Summary
Arabic lacked a large corpus labelled for event modality, meaning potential rather than actual events: obligation, permission, commitment, ability and volition, following Palmer's (2001) taxonomy. Existing modality schemes elsewhere usually depend on theory-heavy guidelines and trained linguists, which keeps them small. The authors collected Egyptian Twitter data that mixes Modern Standard Arabic (MSA) and Egyptian Arabic (EA). They pre-marked candidate triggers by string matching against earlier modality lexicons. Annotators then labelled six attributes through an interactive question flow, where later questions appear or stay hidden depending on earlier answers: sense, polarity, intensification, tense, holders and scopes. Nested holders and merged triggers are derived automatically from those answers. Because no linguistic training is needed, the procedure suits crowdsourcing. Agreement, measured with Krippendorff's alpha, was high and in line with comparable work. The result is a modality resource larger than earlier ones in several languages. It is intended for later machine-learning work on Arabic modality and for finding key political actors on Twitter.

## Key points
- The corpus has 9949 unique tweets with 12,134 highlighted candidate triggers, covering 315 unique trigger types.
- In the majority labels, 7884 candidates are modal and 4250 are non-modal.
  - Polarity: 4733 AFF, 3151 NEG.
  - Intensification: 1565 AMP, 1647 MTG, 4672 AS IS.
  - Tense: 4923 PRS, 2961 PST.
- About 60.5% of triggers have zero-nested holders, meaning the tweet's author is the only holder. Example 6 in the paper has three nested holders.
- Tense agreement was nearly perfect.
  - Holder disagreements came mostly from generic nouns and impersonal pronouns such as "the people" or "one".
  - Scope disagreements came from ambiguous subordinating conjunctions, trigger modifiers and missing punctuation.
- Limitations: no future tense, only declarative mood, and no modality entailment (for example, when a user criticises someone else's stated obligation).

## Interesting ideas
- Sense is decided by asking whether a candidate is synonymous with one of several exemplar sets, instead of applying an abstract definition; the exemplars deliberately mix varieties, single words and multiword expressions, polarities and intensities, which makes them a compact operational stand-in for a category.
- Each label must come with a justification: annotators cannot pick "non-modal" without supplying their own synonym, and they must name the cause of any negation or intensity change; this blocks lazy shortcut answers and produces the reason alongside the label.
- Polarity is computed from several sources: particles, affixes, negative polarity items, negated auxiliaries, inherently negative lexemes, and embedding under a negated epistemic verb; stacked negations flip back to affirmative.
- Holders are represented as a nested chain (the user quotes Obama, who believes something about the Iranians), and the chain is built from a few yes/no questions about quotation and assumption.
- Intensity is treated as a lexical baseline that context can amplify or mitigate through modifiers, coordination, categorical negation, emphatics or epistemic embedding.

## For Mova

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

- **I1** (learn): LLM teacher tiers could be given small, varied exemplar sets per VerbNet class or modal sense and asked a synonymy question, which should give more consistent silver labels than definitions.
- **I2** (learn): requiring teachers or witness parsers to give a reason alongside every label would act as a built-in check and supply raw material for self-induced repair rules.
- **I3** (frames): prag could compute frame polarity explicitly from these sources, so "I don't think it's necessary" does not produce an asserted obligation and the derivation stays explainable.
- **I4** (world): the world of a text could keep each state or desire under a source stack, so answers can say who holds a claim and through whom it is reported.
- **I5** (world): modal strength could be stored as a lexical value in compiled knowledge, with context rules adjusting it, giving graded and traceable obligation or desire strengths.

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

## Institutions

- [University of Illinois Urbana-Champaign](https://md.research.elamur.ai/free/en/universities/university-of-illinois-urbana-champaign/) — University, Urbana, United States · 209 works · 71,394 citations

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## Cite

Cite as: Rania Al-Sabbagh, Roxana Girju and Jana Diesner. 2014. Interactive Annotation for Event Modality in Modern Standard and Egyptian Arabic Tweets. Proceedings of LAW VIII - The 8th Linguistic Annotation Workshop.

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

```bibtex
@inproceedings{alsabbagh2014interactive,
  title = {{Interactive Annotation for Event Modality in Modern Standard and Egyptian Arabic Tweets}},
  author = {Rania Al-Sabbagh, Roxana Girju and Jana Diesner},
  booktitle = {Proceedings of LAW VIII - The 8th Linguistic Annotation Workshop},
  year = {2014},
  doi = {10.3115/v1/w14-4920},
  url = {https://doi.org/10.3115/v1/w14-4920}
}
```

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## References

24 references, 3 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Rania Al-Sabbagh, Jana Diesner and Roxana Girju. 2013. [Using the Semantic-Syntactic Interface for Reliable Arabic Modality Annotation](https://md.research.elamur.ai/free/en/papers/sabbagh-2013-semantic-syntactic-interface-reliable-arabic/). In Proceedings of IJCNLP'13, pages 410-418, October 14-18, 2013, Nagoya, Japan.
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3. Rania Al-Sabbagh, Roxana Girju and Jana Diesner. 2014b. [3arif: A Corpus of Modern Standard and Egyptian Arabic Tweets Annotated for Epistemic Modality Using Interactive Crowdsourcing](https://md.research.elamur.ai/free/en/papers/sabbagh-2014-3arif-corpus-modern-standard-egyptian/). In Proceedings of the 25 th International Conference on Computational Linguistics, August 23-29, 2014, Dublin, Ireland.
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*Updated 2 November 2026*
