NLPRO SIGNED
Natural Language Programming: Turning Text into Executable Code
Total Cost €
0EC-Contrib. €
0Partnership
0Views
0NLPRO 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.
Project "NLPRO" data sheet
The following table provides information about the project.
| Coordinator |
BAR ILAN UNIVERSITY
Organization address contact info |
| 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.
| # | ||||
|---|---|---|---|---|
| 1 | BAR ILAN UNIVERSITY | IL (RAMAT GAN) | coordinator | 1˙089˙199.00 |
| 2 | THE OPEN UNIVERSITY | 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
| 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; 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 (fabio@fabiodisconzi.com) 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.