---
title: "Morphology — papers, page 2"
description: "Morphology: 245 papers of the Elamur Research library · page 2 of 4 · 26–125, the most cited first."
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# 🧩 Morphology

245 papers · page 2 of 4 · 26–125 · the most cited first · [all topics](https://md.research.elamur.ai/free/en/topics/)

How words are built: roots, affixes, inflection, and the analyzers that take them apart.

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26. [**Learning Morphology with Morfette**Grzegorz Chrupala, Georgiana Dinu, Josef van Genabith*2008 · 189 citations*](https://md.research.elamur.ai/free/en/papers/chrupala-2008-learning-morphology-morfette/)
27. [**Semi-supervised learning of morphological paradigms and lexicons**Mans Hulden, Markus Forsberg, Malin Ahlberg*2014 · 188 citations*](https://md.research.elamur.ai/free/en/papers/ahlberg-2014-paradigm-extraction/)
28. [**Arabic Diacritization through Full Morphological Tagging**Nizar Habash, Owen Rambow*2007 · 184 citations*](https://md.research.elamur.ai/free/en/papers/habash-2007-arabic-diacritization-through-full-morphological/)
29. [**Building a Shallow Arabic Morphological Analyser in One Day**Kareem Darwish*2002 · 183 citations*](https://md.research.elamur.ai/free/en/papers/darwish-2002-building-shallow-arabic-morphological-analyser/)
30. [**Knowledge-Free Induction of Inflectional Morphologies**Patrick Schone, Daniel Jurafsky*2001 · 170 citations*](https://md.research.elamur.ai/free/en/papers/schone-2001-knowledge-free-induction-inflectional-morphologies/)
31. [**Morfessor 2.0: Toolkit for statistical morphological segmentation**Peter Smit, Sami Virpioja, Stig-Arne Grönroos, et al.*2014 · 168 citations*](https://md.research.elamur.ai/free/en/papers/smit-2014-morfessor-2-0-toolkit-statistical/)
32. [**Unsupervised discovery of morphologically related words based on orthographic and semantic similarity**Marco Baroni, Johannes Matiasek, Harald Trost*2002 · 144 citations*](https://md.research.elamur.ai/free/en/papers/baroni-2002-unsupervised-discovery-morphologically-related-words/)
33. [**Morphological Annotation of Quranic Arabic**Kais Dukes, Nizar Habash*2010 · 134 citations*](https://md.research.elamur.ai/free/en/papers/dukes-2010-morphological-annotation-quranic-arabic/)
34. [**UniMorph 3.0: Universal Morphology**Arya D. McCarthy, Christo Kirov, Matteo Grella, et al.*2020 · 122 citations*](https://md.research.elamur.ai/free/en/papers/mccarthy-2020-unimorph-3-0-universal-morphology/)
35. [**Data Augmentation for Morphological Reinflection**Miikka Silfverberg, Adam Wiemerslage, Ling Liu, et al.*2017 · 122 citations*](https://md.research.elamur.ai/free/en/papers/silfverberg-2017-data-augmentation-morphological-reinflection/)
36. [**MorphoLex: A derivational morphological database for 70,000 English words**Claudia H. Sánchez-Gutiérrez, Hugo Mailhot, S. Hélène Deacon, et al.*2018 · 115 citations*](https://md.research.elamur.ai/free/en/papers/gutierrez-2018-sanchezgutierrez-morpholex/)
37. [**Dependency Parsing of Modern Standard Arabic with Lexical and Inflectional Features**Yuval Marton, Nizar Habash, Owen Rambow*2013 · 109 citations*](https://md.research.elamur.ai/free/en/papers/marton-2013-dependency-parsing-modern-standard-arabic/)
38. [**Robust, applied morphological generation**Guido Minnen, John Carroll, Darren Pearce*2000 · 106 citations*](https://md.research.elamur.ai/free/en/papers/minnen-2000-robust-applied-morphological-generation/)
39. [**Very-large Scale Parsing and Normalization of Wiktionary Morphological Paradigms**Christo Kirov, John Sylak-Glassman, Roger Que, et al.*2016 · 104 citations*](https://md.research.elamur.ai/free/en/papers/kirov-2016-wiktionary-paradigms/)
40. [**Superbizarre Is Not Superb: Derivational Morphology Improves BERT's Interpretation of Complex Words**Valentin, Hofmann*2021 · 101 citations*](https://md.research.elamur.ai/free/en/papers/hofmann-2021-superbizarre-derivational/)
41. [**An Unsupervised Morpheme-Based HMM for Hebrew Morphological Disambiguation**Meni Adler, Michael Elhadad*2006 · 99 citations*](https://md.research.elamur.ai/free/en/papers/adler-2006-unsupervised-morpheme-based-hmm-hebrew/)
42. [**Issues in Arabic Orthography and Morphology Analysis**Tim Buckwalter*2004 · 98 citations*](https://md.research.elamur.ai/free/en/papers/buckwalter-2004-issues-arabic-orthography-morphology-analysis/)
43. [**Don't Throw Those Morphological Analyzers Away Just Yet: Neural Morphological Disambiguation for Arabic**Nasser Zalmout, Nizar Habash*2017 · 96 citations*](https://md.research.elamur.ai/free/en/papers/zalmout-2017-don-t-throw-those-morphological/)
44. [**Morphological Analysis and Generation for Arabic Dialects**Nizar Habash, Owen Rambow, George Kiraz*2005 · 96 citations*](https://md.research.elamur.ai/free/en/papers/habash-2005-morphological-analysis-generation-arabic-dialects/)
45. [**Multitiered Nonlinear Morphology Using Multitape Finite Automata: A Case Study on Syriac and Arabic**George Anton Kiraz*2000 · 96 citations*](https://md.research.elamur.ai/free/en/papers/kiraz-2000-multitiered-nonlinear-morphology-multitape-finite/)
46. [**Minimally-Supervised Morphological Segmentation using Adaptor Grammars**Kairit Sirts, Sharon Goldwater*2013 · 94 citations*](https://md.research.elamur.ai/free/en/papers/sirts-2013-minimally-supervised-morphological-segmentation-adaptor/)
47. [**Arabic Morphology Using Only Finite-State Operations**Kenneth R. Beesley*1998 · 92 citations*](https://md.research.elamur.ai/free/en/papers/beesley-1998-arabic-morphology-only-finite-state/)
48. [**Automatic training of lemmatization rules that handle morphological changes in pre-, in- and suffixes alike**Bart Jongejan, Hercules Dalianis*2009 · 90 citations*](https://md.research.elamur.ai/free/en/papers/jongejan-2009-automatic-training-lemmatization-rules-that/)
49. [**UniMorph 4.0: Universal Morphology**Khuyagbaatar Batsuren, Omer Goldman, Salam Khalifa*2022 · 82 citations*](https://md.research.elamur.ai/free/en/papers/batsuren-2022-unimorph-4/)
50. [**Language Modeling for Morphologically Rich Languages: Character-Aware Modeling for Word-Level Prediction**Daniela Gerz, Ivan Vulić, Edoardo Ponti, et al.*2018 · 82 citations*](https://md.research.elamur.ai/free/en/papers/gerz-2018-language-modeling-morphologically-rich-languages/)
51. [**A Morphologically Sensitive Clustering Algorithm for Identifying Arabic Roots**Anne N. De Roeck, Waleed Al-Fares*2000 · 78 citations*](https://md.research.elamur.ai/free/en/papers/roeck-2000-morphologically-sensitive-clustering-algorithm-identifying/)
52. [**The SIGMORPHON 2022 Shared Task on Morpheme Segmentation**Khuyagbaatar Batsuren, Gabor Bella, Aryaman Arora*2022 · 71 citations*](https://md.research.elamur.ai/free/en/papers/batsuren-2022-morpheme-segmentation/)
53. [**Improving Arabic Dependency Parsing with Lexical and Inflectional Morphological Features**Yuval Marton, Nizar Habash, Owen Rambow*2010 · 67 citations*](https://md.research.elamur.ai/free/en/papers/marton-2010-improving-arabic-dependency-parsing-lexical/)
54. [**Integrated Morphological and Syntactic Disambiguation for Modern Hebrew**Reut Tsarfaty*2006 · 67 citations*](https://md.research.elamur.ai/free/en/papers/tsarfaty-2006-integrated-morphological-syntactic-disambiguation-modern/)
55. [**Evaluating Various Tokenizers for Arabic Text Classification**Zaid Alyafeai, Maged S. Al-shaibani, Mustafa Ghaleb, et al.*2021 · 66 citations*](https://md.research.elamur.ai/free/en/papers/alyafeai-2021-evaluating-various-tokenizers-arabic-text/)
56. [**A Graph-based Lattice Dependency Parser for Joint Morphological Segmentation and Syntactic Analysis**Wolfgang Seeker, Özlem Çetinoğlu*2015 · 66 citations*](https://md.research.elamur.ai/free/en/papers/seeker-2015-graph-based-lattice-dependency-parser/)
57. [**Multi-Tape Two-Level Morphology: A Case Study in Semitic Non-Linear Morphology**George Anton Kiraz*1994 · 62 citations*](https://md.research.elamur.ai/free/en/papers/kiraz-1994-multi-tape-two-level-morphology/)
58. [**ElixirFM – Implementation of Functional Arabic Morphology**Otakar Smrž*2007 · 61 citations*](https://md.research.elamur.ai/free/en/papers/smrz-2007-elixirfm-implementation-functional-arabic-morphology/)
59. [**Joint Transition-Based Models for Morpho-Syntactic Parsing: Parsing Strategies for MRLs and a Case Study from Modern Hebrew**Amir More, Amit Seker, Victoria Basmova, et al.*2019 · 60 citations*](https://md.research.elamur.ai/free/en/papers/more-2019-joint-transition-based-models-morpho/)
60. [**A global model for joint lemmatization and part-of-speech prediction**Kristina Toutanova, Colin Cherry*2009 · 58 citations*](https://md.research.elamur.ai/free/en/papers/toutanova-2009-global-model-joint-lemmatization-part/)
61. [**AlephBERT: A Hebrew Large Pre-Trained Language Model to Start-off your Hebrew NLP Application With**Amit Seker, Elron Bandel, Dan Bareket, et al.*2021 · 56 citations*](https://md.research.elamur.ai/free/en/papers/seker-2021-alephbert-hebrew-large-pre-trained/)
62. [**MorphyNet: a Large Multilingual Database of Derivational and Inflectional Morphology**Khuyagbaatar Batsuren, Gabor Bella, Fausto Giunchiglia*2021 · 56 citations*](https://md.research.elamur.ai/free/en/papers/batsuren-2021-morphynet/)
63. [**Morphological Tagging: Data vs. Dictionaries**Jan Hajic*2000 · 55 citations*](https://md.research.elamur.ai/free/en/papers/hajic-2000-morphological-tagging-data-vs-dictionaries/)
64. [**Normalisation of Historical Text Using Context-Sensitive Weighted Levenshtein Distance and Compound Splitting**Eva Pettersson, Beáta Megyesi, Joakim Nivre*2013 · 53 citations*](https://md.research.elamur.ai/free/en/papers/pettersson-2013-normalisation-historical-text-context-sensitive/)
65. [**An Arabic Morphological Analyzer and Generator with Copious Features**Dima Taji, Salam Khalifa, Ossama Obeid, et al.*2018 · 52 citations*](https://md.research.elamur.ai/free/en/papers/taji-2018-arabic-morphological-analyzer-generator-copious/)
66. [**What's Wrong with Hebrew NLP? And How to Make it Right**Reut Tsarfaty, Shoval Sadde, Stav Klein, et al.*2019 · 50 citations*](https://md.research.elamur.ai/free/en/papers/tsarfaty-2019-what-s-wrong-hebrew-nlp/)
67. [**Morphological Analysis and Generation of Arabic Nouns: A Morphemic Functional Approach**Mohamed Altantawy, Nizar Habash, Owen Rambow, et al.*2010 · 49 citations*](https://md.research.elamur.ai/free/en/papers/altantawy-2010-morphological-analysis-generation-arabic-nouns/)
68. [**Marrying Universal Dependencies and Universal Morphology**Arya D. McCarthy, Miikka Silfverberg, Ryan Cotterell, et al.*2018 · 48 citations*](https://md.research.elamur.ai/free/en/papers/mccarthy-2018-marrying-universal-dependencies-universal-morphology/)
69. [**Counting the Bugs in ChatGPT's Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language Model**Leonie Weissweiler, Valentin Hofmann, Anjali Kantharuban*2023 · 47 citations*](https://md.research.elamur.ai/free/en/papers/weissweiler-2023-chatgpt-wugs-morphology/)
70. [**Lemmatisation as a Tagging Task**Andrea Gesmundo, Tanja Samardžić*2012 · 47 citations*](https://md.research.elamur.ai/free/en/papers/gesmundo-2012-lemmatisation-as-tagging-task/)
71. [**Choosing an Optimal Architecture for Segmentation and POS-Tagging of Modern Hebrew**Roy Bar-Haim, Khalil Sima'an, Yoad Winter*2005 · 46 citations*](https://md.research.elamur.ai/free/en/papers/haim-2005-choosing-optimal-architecture-segmentation-pos/)
72. [**Joint Diacritization, Lemmatization, Normalization, and Fine-Grained Morphological Tagging**Nasser Zalmout, Nizar Habash*2020 · 44 citations*](https://md.research.elamur.ai/free/en/papers/zalmout-2020-joint-diacritization-lemmatization-normalization-fine/)
73. [**CamelParser: A system for Arabic Syntactic Analysis and Morphological Disambiguation**Anas Shahrour, Salam Khalifa, Dima Taji, et al.*2016 · 44 citations*](https://md.research.elamur.ai/free/en/papers/shahrour-2016-camelparser-system-arabic-syntactic-analysis/)
74. [**An Open-Source Finite State Morphological Transducer for Modern Standard Arabic**Mohammed Attia, Pavel Pecina, Antonio Toral, et al.*2011 · 44 citations*](https://md.research.elamur.ai/free/en/papers/attia-2011-open-source-finite-state-morphological/)
75. [**Noise-Robust Morphological Disambiguation for Dialectal Arabic**Nasser Zalmout, Alexander Erdmann, Nizar Habash*2018 · 42 citations*](https://md.research.elamur.ai/free/en/papers/zalmout-2018-noise-robust-morphological-disambiguation-dialectal/)
76. [**Representations and Architectures in Neural Sentiment Analysis for Morphologically Rich Languages: A Case Study from Modern Hebrew**Adam Amram, Anat Ben David, Reut Tsarfaty*2018 · 40 citations*](https://md.research.elamur.ai/free/en/papers/amram-2018-representations-architectures-neural-sentiment-analysis/)
77. [**A Finite-State Morphological Grammar of Hebrew**Shlomo Yona, Shuly Wintner*2005 · 40 citations*](https://md.research.elamur.ai/free/en/papers/yona-2005-finite-state-morphological-grammar-hebrew/)
78. [**A Simple Joint Model for Improved Contextual Neural Lemmatization**Chaitanya Malaviya, Shijie Wu, Ryan Cotterell*2019 · 39 citations*](https://md.research.elamur.ai/free/en/papers/malaviya-2019-simple-joint-model-improved-contextual/)
79. [**Word Segmentation, Unknown-word Resolution, and Morphological Agreement in a Hebrew Parsing System**Yoav Goldberg, Michael Elhadad*2013 · 39 citations*](https://md.research.elamur.ai/free/en/papers/goldberg-2013-word-segmentation-unknown-word-resolution/)
80. [**Easy-First Dependency Parsing of Modern Hebrew**Yoav Goldberg, Michael Elhadad*2010 · 38 citations*](https://md.research.elamur.ai/free/en/papers/goldberg-2010-easy-first-dependency-parsing-modern/)
81. [**Adversarial Multitask Learning for Joint Multi-Feature and Multi-Dialect Morphological Modeling**Nasser Zalmout, Nizar Habash*2019 · 37 citations*](https://md.research.elamur.ai/free/en/papers/zalmout-2019-adversarial-multitask-learning-joint-multi/)
82. [**Universal Dependencies for Croatian (that work for Serbian, too)**Željko Agić, Nikola Ljubešić*2015 · 37 citations*](https://md.research.elamur.ai/free/en/papers/agic-2015-universal-dependencies-croatian-that-work/)
83. [**Pattern-and-root inflectional morphology: the Arabic broken plural**Alexis Amid Neme, Eric Laporte*2026 · 36 citations*](https://md.research.elamur.ai/free/en/papers/neme-2026-pattern-root-inflectional-morphology-arabic/)
84. [**Morphologically Annotated Corpora for Seven Arabic Dialects: Taizi, Sanaani, Najdi, Jordanian, Syrian, Iraqi and Moroccan**Faisal Alshargi, Shahd Dibas, Sakhar Alkhereyf, et al.*2019 · 34 citations*](https://md.research.elamur.ai/free/en/papers/alshargi-2019-morphologically-annotated-corpora-seven-arabic/)
85. [**Memory-Based Morphological Analysis Generation and Part-of-Speech Tagging of Arabic**Erwin Marsi, Antal van den Bosch, Abdelhadi Soudi*2005 · 33 citations*](https://md.research.elamur.ai/free/en/papers/marsi-2005-memory-based-morphological-analysis-generation/)
86. [**Neural Modeling for Named Entities and Morphology (NEMO2)**Dan Bareket, Reut Tsarfaty*2021 · 32 citations*](https://md.research.elamur.ai/free/en/papers/bareket-2021-neural-modeling-named-entities-morphology/)
87. [**Morphological Disambiguation of Hebrew: A Case Study in Classifier Combination**Danny Shacham, Shuly Wintner*2007 · 32 citations*](https://md.research.elamur.ai/free/en/papers/shacham-2007-morphological-disambiguation-hebrew-case-study/)
88. [**The Hebrew Universal Dependency Treebank: Past, Present and Future**Shoval Sade, Amit Seker, Reut Tsarfaty*2018 · 31 citations*](https://md.research.elamur.ai/free/en/papers/sade-2018-hebrew-universal-dependency-treebank-past/)
89. [**An Accurate Arabic Root-Based Lemmatizer for Information Retrieval Purposes**Tarek El-Shishtawy, Fatma El-Ghannam*2012 · 30 citations*](https://md.research.elamur.ai/free/en/papers/el-shishtawy-2012-accurate-arabic-root-based-lemmatizer/)
90. [**Unsupervised Morphology Rivals Supervised Morphology for Arabic MT**David Stallard, Jacob Devlin, Michael Kayser, et al.*2012 · 30 citations*](https://md.research.elamur.ai/free/en/papers/stallard-2012-unsupervised-morphology-rivals-supervised-morphology/)
91. [**On the Role of Morphological Information for Contextual Lemmatization**Olia Toporkov, Rodrigo Agerri*2024 · 28 citations*](https://md.research.elamur.ai/free/en/papers/toporkov-2024-role-morphological-information-contextual-lemmatization/)
92. [**Fine-Grain Morphological Analyzer and Part-of-Speech Tagger for Arabic Text**Majdi Sawalha, Eric Atwell*2010 · 28 citations*](https://md.research.elamur.ai/free/en/papers/sawalha-2010-fine-grain-morphological-analyzer-part/)
93. [**Nâbra: Syrian Arabic Dialects with Morphological Annotations**Amal Nayouf, Tymaa Hammouda, Mustafa Jarrar, et al.*2023 · 27 citations*](https://md.research.elamur.ai/free/en/papers/nayouf-2023-nabra-syrian-arabic-dialects-morphological/)
94. [**Camelira: An Arabic Multi-Dialect Morphological Disambiguator**Ossama Obeid, Go Inoue, Nizar Habash*2022 · 27 citations*](https://md.research.elamur.ai/free/en/papers/obeid-2022-camelira-arabic-multi-dialect-morphological/)
95. [**A Compact Arabic Lexical Semantics Language Resource Based on the Theory of Semantic Fields**Mohamed Attia, Mohsen Rashwan, Ahmed Ragheb, et al.*2008 · 27 citations*](https://md.research.elamur.ai/free/en/papers/attia-2008-compact-arabic-lexical-semantics-language/)
96. [**A Dictionary and Morphological Analyser for English**G.J. Russell, S.G. Pulman, G.D. Ritchie, et al.*1986 · 27 citations*](https://md.research.elamur.ai/free/en/papers/russell-1986-dictionary-morphological-analyser-english/)
97. [**Challenging Language-Dependent Segmentation for Arabic: An Application to Machine Translation and Part-of-Speech Tagging**Hassan Sajjad, Fahim Dalvi, Nadir Durrani, et al.*2017 · 26 citations*](https://md.research.elamur.ai/free/en/papers/sajjad-2017-challenging-language-dependent-segmentation-arabic/)
98. [**Build Fast and Accurate Lemmatization for Arabic**Hamdy Mubarak*2018 · 25 citations*](https://md.research.elamur.ai/free/en/papers/mubarak-2018-build-fast-accurate-lemmatization-arabic/)
99. [**Morphological Word Embeddings for Arabic Neural Machine Translation in Low-Resource Settings**Pamela Shapiro, Kevin Duh*2018 · 25 citations*](https://md.research.elamur.ai/free/en/papers/shapiro-2018-morphological-word-embeddings-arabic-neural/)
100. [**Semitic Morphological Analysis and Generation Using Finite State Transducers with Feature Structures**Michael Gasser*2009 · 25 citations*](https://md.research.elamur.ai/free/en/papers/gasser-2009-semitic-morphological-analysis-generation-finite/)
101. [**Morphological Analysis and Disambiguation for Gulf Arabic: The Interplay between Resources and Methods**Salam Khalifa, Nasser Zalmout, Nizar Habash*2020 · 24 citations*](https://md.research.elamur.ai/free/en/papers/khalifa-2020-morphological-analysis-disambiguation-gulf-arabic/)
102. [**Nakdan: Professional Hebrew Diacritizer**Avi Shmidman, Shaltiel Shmidman, Moshe Koppel, et al.*2020 · 23 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2020-nakdan-professional-hebrew-diacritizer/)
103. [**Word-Based or Morpheme-Based? Annotation Strategies for Modern Hebrew Clitics**Reut Tsarfaty, Yoav Goldberg*2008 · 23 citations*](https://md.research.elamur.ai/free/en/papers/tsarfaty-2008-word-based-or-morpheme-based/)
104. [**Morphological Inflection: A Reality Check**Jordan Kodner, Sarah Payne, Salam Khalifa, et al.*2023 · 22 citations*](https://md.research.elamur.ai/free/en/papers/kodner-2023-inflection-reality-check/)
105. [**Are we there yet? Encoder-decoder neural networks as cognitive models of English past tense inflection**Maria Corkery, Yevgen Matusevych, Sharon Goldwater*2019 · 22 citations*](https://md.research.elamur.ai/free/en/papers/corkery-2019-are-we-there-yet-encoder/)
106. [**A Pointer Network Architecture for Joint Morphological Segmentation and Tagging**Amit Seker, Reut Tsarfaty*2020 · 21 citations*](https://md.research.elamur.ai/free/en/papers/seker-2020-pointer-network-architecture-joint-morphological/)
107. [**A Rich Morphological Tagger for English: Exploring the Cross-Linguistic Tradeoff Between Morphology and Syntax**Christo Kirov, John Sylak-Glassman, Rebecca Knowles, et al.*2017 · 21 citations*](https://md.research.elamur.ai/free/en/papers/kirov-2017-rich-morphological-tagger-english-exploring/)
108. [**Improving Arabic Dependency Parsing with Form-based and Functional Morphological Features**Yuval Marton, Nizar Habash, Owen Rambow*2011 · 21 citations*](https://md.research.elamur.ai/free/en/papers/marton-2011-improving-arabic-dependency-parsing-form/)
109. [**Leveraging Rule-Based Machine Translation Knowledge for Under-Resourced Neural Machine Translation Models**Daniel Torregrosa, Nivranshu Pasricha, Maraim Masoud, et al.*2019 · 20 citations*](https://md.research.elamur.ai/free/en/papers/torregrosa-2019-leveraging-rule-based-machine-translation/)
110. [**A Distributional and Orthographic Aggregation Model for English Derivational Morphology**Daniel Deutsch, John Hewitt, Dan Roth*2018 · 19 citations*](https://md.research.elamur.ai/free/en/papers/deutsch-2018-distributional-orthographic-aggregation-model-english/)
111. [**Morphological Features for Parsing Morphologically-rich Languages: A Case of Arabic**Jon Dehdari, Lamia Tounsi, Josef van Genabith*2011 · 19 citations*](https://md.research.elamur.ai/free/en/papers/dehdari-2011-morphological-features-parsing-morphologically-rich/)
112. [**Noun Phrase Chunking in Hebrew: Influence of Lexical and Morphological Features**Yoav Goldberg, Meni Adler, Michael Elhadad*2006 · 19 citations*](https://md.research.elamur.ai/free/en/papers/goldberg-2006-noun-phrase-chunking-hebrew-influence/)
113. [**A Comprehensive NLP System for Modern Standard Arabic and Modern Hebrew**Dror Kamir, Naama Soreq, Yoni Neeman*2002 · 19 citations*](https://md.research.elamur.ai/free/en/papers/kamir-2002-comprehensive-nlp-system-modern-standard/)
114. [**Simultaneous Tokenization and Part-Of-Speech Tagging for Arabic without a Morphological Analyzer**Seth Kulick*2010 · 17 citations*](https://md.research.elamur.ai/free/en/papers/kulick-2010-simultaneous-tokenization-part-speech-tagging/)
115. [**Derivational Relations in Arabic WordNet**Mohamed Ali Batita, Mounir Zrigui*2018 · 15 citations*](https://md.research.elamur.ai/free/en/papers/batita-2018-derivational-relations-arabic-wordnet/)
116. [**Creating Linked Data Morphological Language Resources with MMoOn - The Hebrew Morpheme Inventory**Bettina Klimek, Natanael Arndt, Sebastian Krause, et al.*2016 · 15 citations*](https://md.research.elamur.ai/free/en/papers/klimek-2016-creating-linked-data-morphological-language/)
117. [**Hebrew Morphological Preprocessing for Statistical Machine Translation**Nimesh Singh, Nizar Habash*2012 · 15 citations*](https://md.research.elamur.ai/free/en/papers/singh-2012-hebrew-morphological-preprocessing-statistical-machine/)
118. [**Morphotactic Modeling in an Open-source Multi-dialectal Arabic Morphological Analyzer and Generator**Nizar Habash, Reham Marzouk, Christian Khairallah, et al.*2022 · 14 citations*](https://md.research.elamur.ai/free/en/papers/habash-2022-morphotactic-modeling-open-source-multi/)
119. [**Lemmatization and POS-tagging process by using joint learning approach. Experimental results on Classical Armenian, Old Georgian, and Syriac**Chahan Vidal-Gorène, Bastien Kindt*2020 · 14 citations*](https://md.research.elamur.ai/free/en/papers/gorene-2020-lemmatization-pos-tagging-process-joint/)
120. [**Generating Hebrew Verb Morphology by Default Inheritance Hierarchies**Raphael Finkel, Gregory Stump*2002 · 14 citations*](https://md.research.elamur.ai/free/en/papers/finkel-2002-generating-hebrew-verb-morphology-default/)
121. [**Preprocessing Solutions for Detection of Sarcasm and Sentiment for Arabic**Mohamed Lichouri, Mourad Abbas, Besma Benaziz, et al.*2021 · 13 citations*](https://md.research.elamur.ai/free/en/papers/lichouri-2021-preprocessing-solutions-detection-sarcasm-sentiment/)
122. [**Wiktionary Normalization of Translations and Morphological Information**Winston Wu, David Yarowsky*2020 · 12 citations*](https://md.research.elamur.ai/free/en/papers/wu-2020-wiktionary-normalization/)
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125. [**A corpus based morphological analyzer for unvocalized modern Hebrew**Alon Itai, Erel Segal*2003 · 12 citations*](https://md.research.elamur.ai/free/en/papers/itai-2003-corpus-based-morphological-analyzer-unvocalized/)

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