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Opendata, web and dolomites

NLPRO SIGNED

Natural Language Programming: Turning Text into Executable Code

Total Cost €

EC-Contrib. €

Partnership

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NLPRO project word cloud

Explore the words cloud of the NLPRO project. It provides you a very rough idea of what is the project "NLPRO" about.

executable cross online semantics synthesis ai themselves fundamental interpretation humans fragments actually intertwined truly input natural compiler argue limited attracted almost vice respective broad feedback compilers dynamic idea termed texts vast extracts closely cnl environment robotics parsing computers simulation disciplinary se point stone interact native replace unambiguous verification language can leap semantic english engineering basis view grammars tongue extraction feed nl separate questions community human respectively computing languages cognitive nlp action return programming output seemingly software structures learning cnls understanding small stepping coverage programs versa expressivity huge successfully static update endow efforts fundamentally goes inception accept relied capacity strict solutions description

Project "NLPRO" data sheet

The following table provides information about the project.

Coordinator	BAR ILAN UNIVERSITY Organization address address: BAR ILAN UNIVERSITY CAMPUS city: RAMAT GAN postcode: 52900 website: www.biu.ac.il contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.
Coordinator Country	Israel [IL]
Total cost	1˙449˙375 €
EC max contribution	1˙449˙375 € (100%)
Programme	1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
Code Call	ERC-2015-STG
Funding Scheme	ERC-STG
Starting year	2016
Duration (year-month-day)	from 2016-08-01 to 2022-07-31

Partnership

Take a look of project's partnership.

#	participants	country	role	EC contrib. [€]
1	BAR ILAN UNIVERSITY BAR ILAN UNIVERSITY Organization address address: BAR ILAN UNIVERSITY CAMPUS city: RAMAT GAN postcode: 52900 website: www.biu.ac.il contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	IL (RAMAT GAN)	coordinator	1˙089˙199.00
2	THE OPEN UNIVERSITY THE OPEN UNIVERSITY Organization address address: UNIVERSITY ROAD city: RAANANA postcode: n.a. website: http://www-e.openu.ac.il/ contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	IL (RAANANA)	participant	360˙175.00

Map

Project objective

Can we program computers in our native tongue? This idea, termed natural language programming, has attracted attention almost since the inception of computers themselves. From the point of view of software engineering (SE), efforts to program in natural language (NL) have relied thus far on controlled natural languages (CNL) -- small unambiguous fragments of English with strict grammars and limited expressivity. Is it possible to replace CNLs with truly natural, human language? From the point of view of natural language processing (NLP), current technology successfully extracts static information from NL texts. However, human-like NL understanding goes far beyond such extraction -- it requires dynamic interpretation processes which affect, and are affected by, the environment, update states and lead to action. So, is it possible to endow computers with this kind of dynamic NL understanding? These two questions are fundamental to SE and NLP, respectively, and addressing each requires a huge leap forward in the respective field. In this proposal I argue that the solutions to these seemingly separate challenges are actually closely intertwined, and that one community's challenge is the other community's stepping stone for a huge leap, and vice versa. Specifically, I propose to view executable programs in SE as semantic structures in NLP, and use them as the basis for broad-coverage dynamic semantic parsing. My ambitious, cross-disciplinary goal is to develop a new NL compiler based on this novel approach to NL semantics. The NL compiler will accept an NL description as input and return an executable system as output. Moreover, it will continuously improve its NL understanding capacity via online learning that will feed on verification, simulation, synthesis or user feedback. Such dynamic, ever-improving, NL compilers will have vast applications in AI, SE, robotics and cognitive computing and will fundamentally change the way humans and computers interact.

Publications

List of publications.
year	authors and title	journal	last update
2019	Tzuf Paz-Argaman, Reut Tsarfaty RUN through the Streets: A New Dataset and Baseline Models for Realistic Urban Navigation published pages: 6448-6454, ISSN: , DOI: 10.18653/v1/d19-1681	Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)	2020-04-03
2019	Tzuf Paz-Argaman Natural Language Navigation published pages: , ISSN: , DOI:		2020-02-27
2017	Tomer Cagan, Stefam Frank, Reut Tsarfaty Data-Driven Broad-Coverage Grammars for Opinionated Natural Language Generation (ONLG) published pages: , ISSN: , DOI:	Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics	2020-02-27
2018	More , Amir; Ã‡etinoÄŸlu , Ã–zlem; Ã‡Ã¶ltekin , Ã‡aÄŸri; Habash , Nizar; Sagot , BenoÃ®t; Seddah , DjamÃ©; Taji , Dima; Tsarfaty , Reut CoNLL-UL: Universal Morphological Lattices for Universal Dependency Parsing published pages: , ISSN: , DOI:	Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC-2018)	2020-02-27
2018	Amit Seker, Amir More, Reut Tsarfaty Universal Morpho-Syntactic Parsing and the Contribution of Lexica: Analyzing the {ONLP} Lab Submission to the CoNLL 2018 Shared Task published pages: , ISSN: , DOI:	Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies	2020-02-27
2018	Reut Tsarfaty The Natural Language Programming {(NLPRO)} Project: Turning Text into Executable Code published pages: , ISSN: , DOI:	Proceedings of REFSQ-2018 Workshops	2020-02-27
2017	Amir More, Reut Tsarfaty Universal Joint Morph-Syntactic Processing: The Open University of Israel\'s Submission to The CoNLL 2017 Shared Task published pages: , ISSN: , DOI:	Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies	2020-02-27
2018	Adam Amram, Anat ben-David, reut Tsarfaty Representations and Architectures in Neural Sentiment Analysis for Morphologically Rich Languages: A Case Study from Modern Hebrew published pages: , ISSN: , DOI:	Proceedings of the 27th International Conference on Computational Linguistics	2020-02-27

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