Directed by Prof. Reut Tsarfaty
Welcome to the ONLP lab!
We research Natural Language Processing (NLP) foundations, algorithms and applications.
We develop morphological, syntactic and semantic models and we particularly like Processing Hebrew.
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Why ONLP?
Multidisciplinarity
Our team members come from diverse background as Commuter science, theoretical linguistics, computational linguistics, Data science, Software engineers, and more
Multilinguality
We work English, Hebrew, and many other languages, and we take active part in the development of universal parsing resources such as UD (universal dependencies). Currently, we are the only research lab actively developing Infrastructure for Hebrew NLP.
Check out our Hebrew ParserDiversity
Our research team is completely balanced in terms of gender! with male and female researchers at all levels. We come from diverse backgrounds and ages. We care that everyone feels safe and comfortable! Our creative sparks come precisely through that.
Team
Everyone say 'Hi' :-)
PI: Dr. Reut Tsarfaty
Head of the ONLP lab. Interested in natural language programming, morphological, syntactic and semantic parsing. Recipient of ERC-StG Grant #677352 and an ISF grant #1739/26
Dr. Royi Lachmi
Postdoc
Dr. Victoria Basmova
Postdoc.
Lab CTO: Amit Seker
MSc Student.
Shoval Sadde
Linguist.
Dan Bareket
Data Scientist.
Tzuf Argaman
PhD Candidate at Ber-Ilan University. Researching grounded and executable semantic parsing, zero-shot learning and multimodality.
Yochai Gurman
MSc student, looking into cause-effect reasoning and argumentation by day,
secretly interested in computational humor by night
Stav Klein
Linguist, unblackboxing RNNs, semantic parsing of Hebrew with CCG, morphological tagger in Hebrew
Projects
Here is a taste of the projects we are currently working on.
Natural language programming: Turning Text into Executable Code
Funded by an ERC-Starting grant #677352
2016 - 2022
In this project we view the programming task as automatically generating a system based on a verbal description of its behavior. Our task is to semantically parse natural language requirements into a formal executable system, using advanced statistical and deep learning methods
Automatic Broad-Coverage Cross-Linguistic Semantic Parsing
Funded by an ISF research grant #1739/26
2016 - 2020
In this project we use deep learning methods for acquiring broad coverage semantic representations that can accommodate morphological, morphosyntactic and morphosemantic phenomena in the same computational framework
Infrastructure for Hebrew Natural Language Processing
Constantly Ongoing
We develop state-of-the-art open-source Hebrew NLP resources and algorithms, including but not limited to Hebrew morphological and syntactic analysis, sentiment analysis, named-entity recognition and more
Publications
Peer-reviewed articles
Paz-Argrman, Tzuf; Tsarfaty, Reut RUN through the Streets: A New Dataset and Baseline Models for Realistic Urban Navigation. EMNLP 2019
Tsarfaty, Reut; Seker, Amit; Sadde, Shoval; Klein, Stav. What's Wrong with Hebrew NLP? And How to Make it Right. EMNLP 2019 Demo Paper
More, Amir; Seker, Amit; Basmova, Victoria; Tsarfaty, Reut. Joint Transition-Based Models for Morpho-Syntactic Parsing: Parsing Strategies for MRLs and a Case Study from Modern Hebrew. Transactions of the Association for Computational Linguistics 7. Pages 33-48, 2019. MIT Press One Rogers Street, Cambridge, MA 02142-1209 USA
Sadde, Shoval; Seker, Amit; Tsarfaty, Reut. The Hebrew Universal Dependency Treebank: Past Present and Future. In Proceedings of the Second Workshop on Universal Dependencies (UDW 2018). Pages 133-143, 2018
Seker, Amit; More, Amir; Tsarfaty, Reut. Universal Morpho-syntactic Parsing and the Contribution of Lexica: Analyzing the ONLP Lab Submission to the CoNLL 2018 Shared Task. In Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies. Pages 208-215, 2018
Amram, Adam; Ben-David, Anat; Tsarfaty, Reut. Representations and Architectures in Neural Sentiment Analysis for Morphologically Rich Languages: A Case Study from Modern Hebrew. In Proceedings of the 27th International Conference on Computational Linguistics. Pages 2242-2252, 2018
More, Amir; Çetinoğlu, Özlem; Çöltekin, Çağrı; Habash, Nizar; Sagot, Benoît; Seddah, Djamé; Taji, Dima; Tsarfaty, Reut. CoNLL-UL: Universal morphological lattices for Universal Dependency parsing. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC), 2018
Tsarfaty, Reut. The Natural Language Programming (NLPRO) Project: Turning Text into Executable Code. In Proceedings of the REFSQ Workshops, 2018
More, Amir; Tsarfaty, Reut. Universal Joint Morph-Syntactic Processing: The Open University of Israel’s Submission to The CoNLL 2017 Shared Task. In Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies. Pages 253-264, 2017
Cagan, Tomer; Frank, Stefan L; Tsarfaty, Reut. Data-driven broad-coverage grammars for opinionated natural language generation (ONLG). In Proceedings of the International Meeting of the Association for Computational Linguistics, 2017
More, Amir; Tsarfaty, Reut. Data-driven morphological analysis and disambiguation for morphologically rich languages and universal dependencies. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics. Pages 337-348, 2016
Nivre, Joakim; De Marneffe, Marie-Catherine; Ginter, Filip; Goldberg, Yoav; Hajic, Jan; Manning, Christopher D; McDonald, Ryan T; Petrov, Slav; Pyysalo, Sampo; Silveira, Natalia; Tsarfaty, Reut; Zeman, Dan. Universal Dependencies v1: A Multilingual Treebank Collection. In Proceedings of LREC. 2016
Tsarfaty, Reut; Pogrebezky, Ilia; Weiss, Guy; Natan, Yaarit; Szekely, Smadar; Harel, David. Semantic parsing using content and context: A case study from requirements elicitation. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP). Pages 1296-1307, 2014
Seddah, Djamé; Kübler, Sandra; Tsarfaty, Reut. Introducing the SPMRL 2014 shared task on parsing morphologically-rich languages. In Proceedings of the First Joint Workshop on Statistical Parsing of Morphologically Rich Languages and Syntactic Analysis of Non-Canonical Languages. Pages 103-109, 2014
Cagan, Tomer; Frank, Stefan L; Tsarfaty, Reut. Generating subjective responses to opinionated articles in social media: an agenda-driven architecture and a turing-like test. In Proceedings of the Joint Workshop on Social Dynamics and Personal Attributes in Social Media, pages 58-67, 2014
Tsarfaty, Reut. Syntax and Parsing of Semitic Languages. Natural Language Processing of Semitic Languages, 67-128, 2014, Springer, Berlin, Heidelber
Stay in touch with us
Interested in hearing more? Drop us a note
Bar-Ilan University, bldg. 216
Room 002
reut.tsarfaty@biu.ac.il