---
title: "Semantically Motivated Hebrew Verb-Noun Multi-Word Expressions Identification — Liebeskind 2016"
description: "The authors take candidates from four MILA corpora (Knesset, Haaretz, TheMarker and Arutz 7), keep only the 553 that two… 77.4% accuracy. 47 references."
authors: ["Chaya Liebeskind", "Yaakov HaCohen-Kerner"]
year: 2016
venue: "Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers"
source: "https://aclanthology.org/C16-1118/"
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/liebeskind-2016-semantically-motivated-hebrew-verb-noun/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/liebeskind-2016-semantically-motivated-hebrew-verb-noun/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [2016](https://md.research.elamur.ai/free/en/papers/2016/page/4/) / Semantically Motivated Hebrew Verb-Noun Multi-Word Expressions Identification

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

**Authors:** [Chaya Liebeskind](https://md.research.elamur.ai/free/en/authors/chaya-liebeskind/); [Yaakov HaCohen-Kerner](https://md.research.elamur.ai/free/en/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, 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: OpenAlex, 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.

## For Mova

- 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`.

I1 goes into [languages/he/05-verbs.md](https://mova.elamur.ai/free/en/docs/languages/he/05-verbs/). I2 goes into [languages/he/07-syntax.md](https://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.

## Institutions

[🎓**Bar-Ilan University** Ramat Gan · Israel 102 works · 17,587 citations](https://md.research.elamur.ai/free/en/universities/bar-ilan-university/) · [🎓**Jerusalem College of Technology** Jerusalem · Israel 10 works · 145 citations](https://md.research.elamur.ai/free/en/universities/jerusalem-college-of-technology/)

Topics[Hebrew & Aramaic](https://md.research.elamur.ai/free/en/topics/hebrew-aramaic/) · [Semitic languages](https://md.research.elamur.ai/free/en/topics/semitic-languages/) · [Idioms & multiword expressions](https://md.research.elamur.ai/free/en/topics/multiword-expressions/)

## Cite

Cite as Chaya Liebeskind and Yaakov HaCohen-Kerner. 2016. Semantically Motivated Hebrew Verb-Noun Multi-Word Expressions Identification. Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers.

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

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

- [← previous Processing Dialectal Arabic: Exploiting Variability and Similarity to Overcome Challenges and Discover Opportunities](https://md.research.elamur.ai/free/en/papers/diab-2016-processing-dialectal-arabic-exploiting-variability/)
- [next → Speaking to One's Heart: דבר and its Semantic Extension](https://md.research.elamur.ai/free/en/papers/mylonas-2016-speaking-one-s-heart-semantic/)
- [↑ back to papers of 2016](https://md.research.elamur.ai/free/en/papers/2016/page/4/)

## References

47 references, 9 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Meni Adler. 2007. Hebrew Morphological Disambiguation: An Unsupervised Stochastic Word-based Approach. Ph.D. thesis, Ben-Gurion University of the Negev. [find](https://scholar.google.com/scholar?q=Meni+Adler%2E+2007%2E+Hebrew+Morphological+Disambiguation%3A+An+Unsupervised+Stochastic+Word%2Dbased+Approach%2E+Ph%2ED%2E+thesis%2C+Ben%2DGurion+University+of+the+Negev%2E)
2. Hassan Al-Haj and Shuly Wintner. 2010. Identifying multi-word expressions by leveraging morphological and syntactic idiosyncrasy. In Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010), pages 10–18, Beijing, China, August. Coling 2010 Organizing Committee. [find](https://scholar.google.com/scholar?q=Hassan+Al%2DHaj+and+Shuly+Wintner%2E+2010%2E+Identifying+multi%2Dword+expressions+by+leveraging+morphological+and+syntactic+idiosyncrasy%2E+In+Proceedings+of+the+23rd+International+Conference+on+Computational+L)
3. Hassan Al-Haj. 2009. Hebrew multiword expressions: Linguistic properties, lexical representation, morphological processing, and automatic acquisition. Ph.D. thesis, University of Haifa. [find](https://scholar.google.com/scholar?q=Hassan+Al%2DHaj%2E+2009%2E+Hebrew+multiword+expressions%3A+Linguistic+properties%2C+lexical+representation%2C+morphological+processing%2C+and+automatic+acquisition%2E+Ph%2ED%2E+thesis%2C+University+of+Haifa%2E)
4. Timothy Baldwin. 2005. Deep lexical acquisition of verb-particle constructions. 19(4):398–414, October. Comput. [find](https://scholar.google.com/scholar?q=Timothy+Baldwin%2E+2005%2E+Deep+lexical+acquisition+of+verb%2Dparticle+constructions%2E+19%284%29%3A398%E2%80%93414%2C+October%2E+Comput%2E)
5. Speech Lang., Roy Bar-haim, Khalil Sima’an, and Yoad Winter. 2008. Part-of-speech tagging of modern hebrew text. Natural Language Engineering, 14(2):223–251, April. [find](https://scholar.google.com/scholar?q=Speech+Lang%2E%2C+Roy+Bar%2Dhaim%2C+Khalil+Sima%E2%80%99an%2C+and+Yoad+Winter%2E+2008%2E+Part%2Dof%2Dspeech+tagging+of+modern+hebrew+text%2E+Natural+Language+Engineering%2C+14%282%29%3A223%E2%80%93251%2C+April%2E)
6. Marco Baroni and Roberto Zamparelli. 2010. Nouns are vectors, adjectives are matrices: Representing adjective-noun constructions in semantic space. In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pages 1183–1193. Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Marco+Baroni+and+Roberto+Zamparelli%2E+2010%2E+Nouns+are+vectors%2C+adjectives+are+matrices%3A+Representing+adjective%2Dnoun+constructions+in+semantic+space%2E+In+Proceedings+of+the+2010+Conference+on+Empirical+M)
7. Eduard Bejcek, Pavel Stranák, and Pavel Pecina. 2013. Syntactic identification of occurrences of multiword expressions in text using a lexicon with dependency structures. In Proceedings of the 9th Workshop on Multiword Expressions, pages 106–115. [find](https://scholar.google.com/scholar?q=Eduard+Bejcek%2C+Pavel+Strana%CC%81k%2C+and+Pavel+Pecina%2E+2013%2E+Syntactic+identification+of+occurrences+of+multiword+expressions+in+text+using+a+lexicon+with+dependency+structures%2E+In+Proceedings+of+the+9th+Wo)
8. Chris Biemann and Eugenie Giesbrecht. 2011. Distributional semantics and compositionality 2011: Shared task description and results. In Proceedings of the workshop on distributional semantics and compositionality, pages 21–28. Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Chris+Biemann+and+Eugenie+Giesbrecht%2E+2011%2E+Distributional+semantics+and+compositionality+2011%3A+Shared+task+description+and+results%2E+In+Proceedings+of+the+workshop+on+distributional+semantics+and+comp)
9. Dhouha Bouamor, Nasredine Semmar, and Pierre Zweigenbaum. 2012. Identifying bilingual multi-word expressions for statistical machine translation. In LREC, pages 674–679. [find](https://scholar.google.com/scholar?q=Dhouha+Bouamor%2C+Nasredine+Semmar%2C+and+Pierre+Zweigenbaum%2E+2012%2E+Identifying+bilingual+multi%2Dword+expressions+for+statistical+machine+translation%2E+In+LREC%2C+pages+674%E2%80%93679%2E)
10. Siham Boulaknadel, Be’atrice Daille, and Driss Aboutajdine. 2008. A multi-word term extraction program for arabic language. In LREC, pages 1485–1488. European Language Resources Association. [find](https://scholar.google.com/scholar?q=Siham+Boulaknadel%2C+Be%E2%80%99atrice+Daille%2C+and+Driss+Aboutajdine%2E+2008%2E+A+multi%2Dword+term+extraction+program+for+arabic+language%2E+In+LREC%2C+pages+1485%E2%80%931488%2E+European+Language+Resources+Association%2E)
11. Daoud Clarke. 2009. Context-theoretic semantics for natural language: an overview. In Proceedings of the Workshop on Geometrical Models of Natural Language Semantics, pages 112–119. Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Daoud+Clarke%2E+2009%2E+Context%2Dtheoretic+semantics+for+natural+language%3A+an+overview%2E+In+Proceedings+of+the+Workshop+on+Geometrical+Models+of+Natural+Language+Semantics%2C+pages+112%E2%80%93119%2E+Association+for+Co)
12. Trevor Cohen, Roger Schvaneveldt, and Dominic Widdows. 2010. Reflective random indexing and indirect inference: A scalable method for discovery of implicit connections. Journal of biomedical informatics, 43(2):240– 256. [find](https://scholar.google.com/scholar?q=Trevor+Cohen%2C+Roger+Schvaneveldt%2C+and+Dominic+Widdows%2E+2010%2E+Reflective+random+indexing+and+indirect+inference%3A+A+scalable+method+for+discovery+of+implicit+connections%2E+Journal+of+biomedical+informati)
13. J. Cohen. 1960. A Coefficient of Agreement for Nominal Scales. Educational and Psychological Measurement, 20(1):37. [find](https://scholar.google.com/scholar?q=J%2E+Cohen%2E+1960%2E+A+Coefficient+of+Agreement+for+Nominal+Scales%2E+Educational+and+Psychological+Measurement%2C+20%281%29%3A37%2E)
14. Paul Deane. 2005. A nonparametric method for extraction of candidate phrasal terms. In Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, pages 605–613. Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Paul+Deane%2E+2005%2E+A+nonparametric+method+for+extraction+of+candidate+phrasal+terms%2E+In+Proceedings+of+the+43rd+Annual+Meeting+on+Association+for+Computational+Linguistics%2C+pages+605%E2%80%93613%2E+Association+f)
15. Gaël Dias, Sylvie Guilloré, and JG Pereira Lopes. 1999. Language independent automatic acquisition of rigid multiword units from unrestricted text corpora. Traitement Automatique des Langues Naturelles, Institut dE-tudes Scientifiques, Cargèse, France, pages 333–339. [find](https://scholar.google.com/scholar?q=Gae%CC%88l+Dias%2C+Sylvie+Guillore%CC%81%2C+and+JG+Pereira+Lopes%2E+1999%2E+Language+independent+automatic+acquisition+of+rigid+multiword+units+from+unrestricted+text+corpora%2E+Traitement+Automatique+des+Langues+Naturel)
16. Meghdad Farahmand and Joakim Nivre. 2015. Modeling the statistical idiosyncrasy of multiword expressions. In Proceedings of NAACL-HLT, pages 34–38. [find](https://scholar.google.com/scholar?q=Meghdad+Farahmand+and+Joakim+Nivre%2E+2015%2E+Modeling+the+statistical+idiosyncrasy+of+multiword+expressions%2E+In+Proceedings+of+NAACL%2DHLT%2C+pages+34%E2%80%9338%2E)
17. Afsaneh Fazly and Suzanne Stevenson. 2006. Automatically constructing a lexicon of verb phrase idiomatic combinations. In Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics (EACL), pages 337–344, Trento Italy. [our card](https://md.research.elamur.ai/free/en/papers/fazly-2006-automatically-constructing-lexicon-verb-phrase/)
18. Spence Green, Marie-Catherine de Marneffe, and Christopher D. Manning. 2013. Parsing models for identifying multiword expressions. Computational Linguistics, 39(1):195–227, March. [find](https://scholar.google.com/scholar?q=Spence+Green%2C+Marie%2DCatherine+de+Marneffe%2C+and+Christopher+D%2E+Manning%2E+2013%2E+Parsing+models+for+identifying+multiword+expressions%2E+Computational+Linguistics%2C+39%281%29%3A195%E2%80%93227%2C+March%2E)
19. Edward Grefenstette and Mehrnoosh Sadrzadeh. 2011. Experimental support for a categorical compositional distributional model of meaning. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, pages 1394–1404. Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Edward+Grefenstette+and+Mehrnoosh+Sadrzadeh%2E+2011%2E+Experimental+support+for+a+categorical+compositional+distributional+model+of+meaning%2E+In+Proceedings+of+the+Conference+on+Empirical+Methods+in+Natura)
20. Emiliano Guevara. 2011. Computing semantic compositionality in distributional semantics. In Proceedings of the Ninth International Conference on Computational Semantics, IWCS ’11, pages 135–144, Stroudsburg, PA, USA. Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Emiliano+Guevara%2E+2011%2E+Computing+semantic+compositionality+in+distributional+semantics%2E+In+Proceedings+of+the+Ninth+International+Conference+on+Computational+Semantics%2C+IWCS+%E2%80%9911%2C+pages+135%E2%80%93144%2C+Strou)
21. Mark Hall, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, and Ian H. Witten. 2009. The weka data mining software: An update. SIGKDD Explor. Newsl., 11(1):10–18, November. [find](https://scholar.google.com/scholar?q=Mark+Hall%2C+Eibe+Frank%2C+Geoffrey+Holmes%2C+Bernhard+Pfahringer%2C+Peter+Reutemann%2C+and+Ian+H%2E+Witten%2E+2009%2E+The+weka+data+mining+software%3A+An+update%2E+SIGKDD+Explor%2E+Newsl%2E%2C+11%281%29%3A10%E2%80%9318%2C+November%2E)
22. M. Hall. 1998. Correlation-based feature subset selection for machine learning. Ph.D. thesis, Department of Computer Science, University of Waikato, Hamilton, New Zealand. [find](https://scholar.google.com/scholar?q=M%2E+Hall%2E+1998%2E+Correlation%2Dbased+feature+subset+selection+for+machine+learning%2E+Ph%2ED%2E+thesis%2C+Department+of+Computer+Science%2C+University+of+Waikato%2C+Hamilton%2C+New+Zealand%2E)
23. E. B. Hunt, J. Marin, and P. J. Stone. 1966. Experiments in Induction. Academic Press, New York. [find](https://scholar.google.com/scholar?q=E%2E+B%2E+Hunt%2C+J%2E+Marin%2C+and+P%2E+J%2E+Stone%2E+1966%2E+Experiments+in+Induction%2E+Academic+Press%2C+New+York%2E)
24. Alon Itai and Shuly Wintner. 2008. Language resources for hebrew. Language Resources and Evaluation, 42(1):75–98. [find](https://scholar.google.com/scholar?q=Alon+Itai+and+Shuly+Wintner%2E+2008%2E+Language+resources+for+hebrew%2E+Language+Resources+and+Evaluation%2C+42%281%29%3A75%E2%80%9398%2E)
25. Ray Jackendoff. 1997. The architecture of the language faculty. Number 28. MIT Press. [find](https://scholar.google.com/scholar?q=Ray+Jackendoff%2E+1997%2E+The+architecture+of+the+language+faculty%2E+Number+28%2E+MIT+Press%2E)
26. John S. Justeson and Slava M. Katz. 1995. Technical terminology: some linguistic properties and an algorithm for identification in text. Natural Language Engineering, 1(1):9–27. [find](https://scholar.google.com/scholar?q=John+S%2E+Justeson+and+Slava+M%2E+Katz%2E+1995%2E+Technical+terminology%3A+some+linguistic+properties+and+an+algorithm+for+identification+in+text%2E+Natural+Language+Engineering%2C+1%281%29%3A9%E2%80%9327%2E)
27. Graham Katz and Eugenie Giesbrecht. 2006. Automatic identification of non-compositional multi-word expressions using latent semantic analysis. In Proceedings of the Workshop on Multiword Expressions: Identifying and Exploiting Underlying Properties, pages 12–19. Association for Computational Linguistics. [our card](https://md.research.elamur.ai/free/en/papers/katz-2006-automatic-identification-non-compositional-multi/)
28. Lili Kotlerman, Ido Dagan, Idan Szpektor, and Maayan Zhitomirsky-Geffet. 2010. Directional distributional similarity for lexical inference. Natural Language Engineering, 16(4):359–389. [find](https://scholar.google.com/scholar?q=Lili+Kotlerman%2C+Ido+Dagan%2C+Idan+Szpektor%2C+and+Maayan+Zhitomirsky%2DGeffet%2E+2010%2E+Directional+distributional+similarity+for+lexical+inference%2E+Natural+Language+Engineering%2C+16%284%29%3A359%E2%80%93389%2E)
29. J. Richard Landis and Gary G. Koch. 1977. The measurement of observer agreement for categorical data. Biometrics, 33(1):159–174. [find](https://scholar.google.com/scholar?q=J%2E+Richard+Landis+and+Gary+G%2E+Koch%2E+1977%2E+The+measurement+of+observer+agreement+for+categorical+data%2E+Biometrics%2C+33%281%29%3A159%E2%80%93174%2E)
30. Chaya Liebeskind and Yaakov HaCohen-Kerner. 2016. A lexical resource of hebrew verb-noun multi-word expressions. In Proceedings of the Tenth International Conference on Language Resources and Evaluation, LREC’16, pages 522–527, Portoroz, Slovenia, may. European Language Resources Association (ELRA). [our card](https://md.research.elamur.ai/free/en/papers/liebeskind-2016-lexical-resource-hebrew-verb-noun/)
31. Kevin Lund and Curt Burgess. 1996. Producing high-dimensional semantic spaces from lexical co-occurrence. Behavior Research Methods, Instruments, & Computers, 28(2):203–208. [find](https://scholar.google.com/scholar?q=Kevin+Lund+and+Curt+Burgess%2E+1996%2E+Producing+high%2Ddimensional+semantic+spaces+from+lexical+co%2Doccurrence%2E+Behavior+Research+Methods%2C+Instruments%2C+%26+Computers%2C+28%282%29%3A203%E2%80%93208%2E)
32. Quinn McNemar. 1947. Note on the sampling error of the difference between correlated proportions or percentages. Psychometrika, 12(2):153–157. [find](https://scholar.google.com/scholar?q=Quinn+McNemar%2E+1947%2E+Note+on+the+sampling+error+of+the+difference+between+correlated+proportions+or+percentages%2E+Psychometrika%2C+12%282%29%3A153%E2%80%93157%2E)
33. Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013. Distributed representations of words and phrases and their compositionality. In Advances in neural information processing systems, pages 3111–3119. [our card](https://md.research.elamur.ai/free/en/papers/mikolov-2013-distributed-representations-words-phrases-their/)
34. Pavel Pecina and Pavel Schlesinger. 2006. Combining association measures for collocation extraction. In Proceedings of the COLING/ACL on Main Conference Poster Sessions, COLING-ACL ’06, pages 651–658, Stroudsburg, PA, USA. Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Pavel+Pecina+and+Pavel+Schlesinger%2E+2006%2E+Combining+association+measures+for+collocation+extraction%2E+In+Proceedings+of+the+COLING%2FACL+on+Main+Conference+Poster+Sessions%2C+COLING%2DACL+%E2%80%9906%2C+pages+651%E2%80%93658%2C)
35. Pavel Pecina. 2010. Lexical association measures and collocation extraction. Language Resources and Evaluation, 44:137–158. [find](https://scholar.google.com/scholar?q=Pavel+Pecina%2E+2010%2E+Lexical+association+measures+and+collocation+extraction%2E+Language+Resources+and+Evaluation%2C+44%3A137%E2%80%93158%2E)
36. Douglas L. T. Rohde, Laura M. Gonnerman, and David C. Plaut. 2006. An improved model of semantic similarity based on lexical co-occurence. Communications of the ACM, 8:627–633. [find](https://scholar.google.com/scholar?q=Douglas+L%2E+T%2E+Rohde%2C+Laura+M%2E+Gonnerman%2C+and+David+C%2E+Plaut%2E+2006%2E+An+improved+model+of+semantic+similarity+based+on+lexical+co%2Doccurence%2E+Communications+of+the+ACM%2C+8%3A627%E2%80%93633%2E)
37. Ivan A. Sag, Timothy Baldwin, Francis Bond, Ann A. Copestake, and Dan Flickinger. 2002. Multiword expressions: A pain in the neck for nlp. In Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing, CICLing ’02, pages 1–15, London, UK, UK. Springer-Verlag. [our card](https://md.research.elamur.ai/free/en/papers/sag-2002-multiword-expressions-pain-neck-nlp/)
38. Magnus Sahlgren. 2005. An introduction to random indexing. In Methods and applications of semantic indexing workshop at the 7th international conference on terminology and knowledge engineering, TKE, volume 5. [find](https://scholar.google.com/scholar?q=Magnus+Sahlgren%2E+2005%2E+An+introduction+to+random+indexing%2E+In+Methods+and+applications+of+semantic+indexing+workshop+at+the+7th+international+conference+on+terminology+and+knowledge+engineering%2C+TKE%2C+)
39. Bahar Salehi, Paul Cook, and Timothy Baldwin. 2015. A word embedding approach to predicting the compositionality of multiword expressions. In Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 977–983. [find](https://scholar.google.com/scholar?q=Bahar+Salehi%2C+Paul+Cook%2C+and+Timothy+Baldwin%2E+2015%2E+A+word+embedding+approach+to+predicting+the+compositionality+of+multiword+expressions%2E+In+Proceedings+of+the+2015+Conference+of+the+North+American+C)
40. Livnat Herzig Sheinfux, Tali Arad Greshler, Nurit Melnik, and Shuly Wintner. 2015. Hebrew verbal multi-word expressions. In Proceedings of the 22nd international conference on Head-Driven Phrase Structure Grammar (HPSG 2015), pages 123–136. [find](https://scholar.google.com/scholar?q=Livnat+Herzig+Sheinfux%2C+Tali+Arad+Greshler%2C+Nurit+Melnik%2C+and+Shuly+Wintner%2E+2015%2E+Hebrew+verbal+multi%2Dword+expressions%2E+In+Proceedings+of+the+22nd+international+conference+on+Head%2DDriven+Phrase+Struc)
41. Richard Socher, Brody Huval, Christopher D Manning, and Andrew Y Ng. 2012. Semantic compositionality through recursive matrix-vector spaces. In Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pages 1201–1211. Association for Computational Linguistics. [our card](https://md.research.elamur.ai/free/en/papers/socher-2012-semantic-compositionality-through-recursive-matrix/)
42. Caroline Sporleder and Linlin Li. 2009. Unsupervised recognition of literal and non-literal use of idiomatic expressions. In Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics, pages 754–762. Association for Computational Linguistics. [our card](https://md.research.elamur.ai/free/en/papers/sporleder-2009-unsupervised-recognition-literal-non-literal/)
43. Yulia Tsvetkov and Shuly Wintner. 2012. Extraction of multi-word expressions from small parallel corpora. Natural Language Engineering, 18(04):549–573. [find](https://scholar.google.com/scholar?q=Yulia+Tsvetkov+and+Shuly+Wintner%2E+2012%2E+Extraction+of+multi%2Dword+expressions+from+small+parallel+corpora%2E+Natural+Language+Engineering%2C+18%2804%29%3A549%E2%80%93573%2E)
44. Yulia Tsvetkov and Shuly Wintner. 2014. Identification of multiword expressions by combining multiple linguistic information sources. Computational Linguistics, 40(2):449–468. [find](https://scholar.google.com/scholar?q=Yulia+Tsvetkov+and+Shuly+Wintner%2E+2014%2E+Identification+of+multiword+expressions+by+combining+multiple+linguistic+information+sources%2E+Computational+Linguistics%2C+40%282%29%3A449%E2%80%93468%2E)
45. Julie Weeds and David Weir. 2003. A general framework for distributional similarity. In Proceedings of the 2003 conference on Empirical methods in natural language processing, pages 81–88. Association for Computational Linguistics. [our card](https://md.research.elamur.ai/free/en/papers/weeds-2003-general-framework-distributional-similarity/)
46. Ian H. Witten and Eibe Frank. 2005. Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems). Morgan Kaufmann Publishers Inc., San Francisco, CA, USA. [find](https://scholar.google.com/scholar?q=Ian+H%2E+Witten+and+Eibe+Frank%2E+2005%2E+Data+Mining%3A+Practical+Machine+Learning+Tools+and+Techniques%2C+Second+Edition+%28Morgan+Kaufmann+Series+in+Data+Management+Systems%29%2E+Morgan+Kaufmann+Publishers+Inc%2E%2C+S)
47. Shlomo Yona and Shuly Wintner. 2008. A finite-state morphological grammar of hebrew. Natural Language Engineering, 14:173–190, 4. [our card](https://md.research.elamur.ai/free/en/papers/yona-2005-finite-state-morphological-grammar-hebrew/)