Opendata, web and dolomites


Natural Language Programming: Turning Text into Executable Code

Total Cost €


EC-Contrib. €






 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.

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

Project "NLPRO" data sheet

The following table provides information about the project.


Organization address
postcode: 52900

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


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    BAR ILAN UNIVERSITY IL (RAMAT GAN) coordinator 1˙089˙199.00
2    THE OPEN UNIVERSITY IL (RAANANA) participant 360˙175.00


 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.


year authors and title journal last update
List of publications.
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:
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; Çetinoğlu , Özlem; Çöltekin , Çağri; Habash , Nizar; Sagot , Benoît; Seddah , Djamé; 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

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "NLPRO" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email ( and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "NLPRO" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.1.1.)

SuperH (2019)

Discovery and Characterization of Hydrogen-Based High-Temperature Superconductors

Read More  

Neurovulnerability (2019)

Molecular mechanisms underlying selective neuronal death in motor neuron diseases

Read More  

InsideChromatin (2019)

Towards Realistic Modelling of Nucleosome Organization Inside Functional Chromatin Domains

Read More