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# Modeling Morphosyntactic Agreement in Constituency-Based Parsing of Modern Hebrew

**Authors:** [Reut Tsarfaty](https://md.mova.elamur.ai/free/en/docs/papers/authors/reut-tsarfaty/); [Khalil Sima'an](https://md.mova.elamur.ai/free/en/docs/papers/authors/khalil-sima-an/) · **Year:** 2010 · **Venue:** Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages **Link:** [aclanthology.org/W10-1405](https://aclanthology.org/W10-1405/) · library `aclbulk-2010-tsarfaty-modeling-morphosyntactic-agreement-constituency-based` · **Licence:** [CC BY-NC-SA 3.0](https://creativecommons.org/licenses/by-nc-sa/3.0/) (ACL Anthology, before 2016) — summary only

[**13** citations](https://openalex.org/works?filter=cites:W2142220626) openalex · 2026-10-18[**8** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/aclbulk-2010-tsarfaty-modeling-morphosyntactic-agreement-constituency-based/) of the 140673 papers whose bibliographies we read[Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages](https://aclanthology.org/volumes/W10-14/)[licence](https://creativecommons.org/licenses/by-nc-sa/3.0/)

- [Publisher's page](https://aclanthology.org/W10-1405/)
- [PDF](https://aclanthology.org/W10-1405.pdf)
- [OpenAlex](https://openalex.org/W2142220626)

**Authors (2)**

1. [Reut Tsarfaty](https://openalex.org/A5063283689) [ORCID](https://orcid.org/0000-0001-6406-6568) · h 24 · 2886 citations · 217 works
2. [Khalil Sima'an](https://openalex.org/A5034829413) h 23 · 2429 citations · 168 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 question is whether agreement features (gender, number, person, definiteness, accusativity) help a statistical parser of Hebrew, and how they should be represented. The authors compare two constituency models on the Hebrew treebank, parsing gold-tagged sentences: a state-split model that puts morphology into the category labels (SP-AGR), and an extension of the Relational-Realizational model (RR-AGR) that separates grammatical function from its realisation and marks the agreement controller and the domain (the clause) with its features. Naive state-splits with agreement features get worse as features are added, sometimes sharply with gender (for example from about 80 to 64 F1 on one setting). The RR model improves as features are added, and the best setting (grandparent labels, gender, definiteness and accusativity) reaches F1 84.13 on sentences under 40 words, the best Hebrew result reported at the time. The authors read the gap as a sparseness effect: the RR parameters capture functional patterns that do not depend on word order.

## Ideas

- I1. Agreement as a checked relation over the tree: for a subject and its verb, and for a predicate and its subject, compare gender, number and person of controller and target. Run it first as a rule over the converted Hebrew trees to count violations, then use the result as a feature or as a validator in `prag`.
- I2. Use the morphology of all co-heads and function words in a phrase, not only of its head. The authors find that gender percolates through the head while definiteness and accusativity come from other words, and that adding only the head tag hurts. A Mova feature for a phrase should therefore be a set of morphological values gathered from the phrase, held in a `BTreeSet` so the result is deterministic.
- I3. Before adding a feature, measure its sparseness: report the number of distinct rule types and the F1 at each feature set, as Table 1 does. This is the cheapest guard against the drop the paper shows.

## For Mova

I1 goes into [05. The verb: system, binyanim, tense and use](https://md.mova.elamur.ai/free/en/docs/languages/he/05-verbs/) (subject-verb agreement) and [Nouns, adjectives, pronouns and numerals](https://md.mova.elamur.ai/free/en/docs/languages/he/04-nouns-adjectives-pronouns/) (predicate and copula agreement). I2 is a design point for `prag` and `world` when a phrase has several morphological carriers. I3 is a rule for any `gparse` or rule-based experiment on `treebanks/he/`. The paper parses Modern Hebrew with a constituency model, so only the ideas transfer.

## Cite

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

```
@inproceedings{tsarfaty2010modeling,
  title = {{Modeling Morphosyntactic Agreement in Constituency-Based Parsing of Modern Hebrew}},
  author = {Tsarfaty, Reut and Sima'an, Khalil},
  booktitle = {Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages},
  year = {2010},
  url = {https://aclanthology.org/W10-1405/}
}
```

- [← previous Towards multi-lingual summarization: A comparative analysis of sentence extraction methods on English and Hebrew corpora](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2010-litvak-multi-lingual-summarization-comparative-analysis/)
- [next → Joint Hebrew Segmentation and Parsing using a PCFGLA Lattice Parser](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2011-goldberg-joint-hebrew-segmentation-parsing-pcfgla/)
- [↑ back to Modern Hebrew](https://md.mova.elamur.ai/free/en/docs/papers/he/)

## References

20 references, 5 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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