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# Semantically Motivated Hebrew Verb-Noun Multi-Word Expressions Identification

**Authors:** [Chaya Liebeskind](https://md.mova.elamur.ai/free/en/docs/papers/authors/chaya-liebeskind/); [Yaakov HaCohen-Kerner](https://md.mova.elamur.ai/free/en/docs/papers/authors/yaakov-hacohen-kerner/) · **Year:** 2016 · **Venue:** Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 1242–1253 **Link:** [aclanthology.org/C16-1118](https://aclanthology.org/C16-1118/) · library `aclbulk-2016-liebeskind-semantically-motivated-hebrew-verb-noun` · **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)

[**2** citations](https://openalex.org/works?filter=cites:W2578274835) openalex-snapshot · 2026-10-14[Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers](https://aclanthology.org/volumes/C16-1/)[licence](https://creativecommons.org/licenses/by/4.0/)

- [Publisher's page](https://aclanthology.org/C16-1118/)
- [PDF](https://aclanthology.org/C16-1118.pdf)
- [OpenAlex](https://openalex.org/W2578274835)

**Authors (2)**

1. [Chaya Liebeskind](https://openalex.org/A5048937508) [ORCID](https://orcid.org/0000-0003-0476-3796) · [Semantic Scholar](https://www.semanticscholar.org/author/2601200) · h 10 · 325 citations · 113 works
2. Yaakov HaCohen-Kerner

Citations and author metrics from openalex-snapshot (2026-10-14); authors with the same name are not always told apart.

## What it is about

The paper decides, for candidate Hebrew bigrams and trigrams that pair a verb with a noun, whether they are multi-word expressions (VN-MWE) or not. The authors take candidates from four MILA corpora (Knesset, Haaretz, TheMarker and Arutz 7), keep only the 553 that two annotators labelled the same way (kappa 0.59; 306 MWEs, 247 non-MWEs), and describe each with 206 features in three sets. The linguistic set covers POS patterns, prefixes and constituent order; the statistical set covers frequencies and association measures such as PMI and log-likelihood; the semantic set compares the two words in five vector spaces (HAL, COALS, random indexing, reflective random indexing and word embeddings). With a random forest and 10-fold cross-validation, the semantic set alone reaches 77.4% accuracy, against 73.96% for the linguistic set and 72.51% for the statistical one. All three sets together reach 80.47% (F 0.795). Among the semantic spaces, the order-sensitive HAL space performs best (75.04%). The main errors are light verbs (such as "get information") and domain-frequent pairs.

## Ideas

- I1. A light-verb list for the MWE step: the false positives came from light verbs, which pair freely with many nouns and so look like collocations. A table of Hebrew light verbs (for example la-ʿasot, "to do") marks a verb-noun pair as light, so that it is checked separately before it is called an expression.
- I2. Constituent order as a rule: the authors report that 82% of their VN-MWEs do not allow the order of the two words to change, and 87% have non-compositional syntax. In a UD tree, a verb with an object whose order cannot change, and whose pair is in the lexicon, is an MWE candidate. Implement the rule and measure it on a gold set.
- I3. An order-sensitive co-occurrence count: HAL, which counts neighbours by side and distance, was the best semantic space here, and the authors link this to word order. A count of this kind over the Mova corpus gives a feature for verb-noun pairs in the frames of `world`.

## 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/). I2 goes into [7. Syntax](https://md.mova.elamur.ai/free/en/docs/languages/he/07-syntax/) as an MWE rule over the parser output. I3 is a feature for the frames in `world`. The 553-item labelled set, if obtained, is a test set for I2 and I3.

## Cite

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

```
@inproceedings{liebeskind2016semantically,
  title = {{Semantically Motivated Hebrew Verb-Noun Multi-Word Expressions Identification}},
  author = {Liebeskind, Chaya and HaCohen-Kerner, Yaakov},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
  year = {2016},
  url = {https://aclanthology.org/C16-1118/}
}
```

- [← previous Innovation of Verbs in Hebrew](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2014-ornan-innovation-verbs-hebrew/)
- [next → NLP in the DH pipeline: Transfer-learning to a Chronolect](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2021-rubinstein-nlp-dh-pipeline-transfer-learning/)
- [↑ back to Modern Hebrew](https://md.mova.elamur.ai/free/en/docs/papers/he/)

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