NLP Lean Programming Framework: Developing NLP Applications More Effectively

Marc Schreiber, Bodo Kraft, Albert Zündorf


Abstract
This paper presents NLP Lean Programming framework (NLPf), a new framework for creating custom Natural Language Processing (NLP) models and pipelines by utilizing common software development build systems. This approach allows developers to train and integrate domain-specific NLP pipelines into their applications seamlessly. Additionally, NLPf provides an annotation tool which improves the annotation process significantly by providing a well-designed GUI and sophisticated way of using input devices. Due to NLPf’s properties developers and domain experts are able to build domain-specific NLP application more effectively. Project page: https://gitlab.com/schrieveslaach/NLPf Video Tutorial: https://www.youtube.com/watch?v=44UJspVebTA (Demonstration starts at 11:40 min) This paper is related to: - Interfaces and resources to support linguistic annotation - Software architectures and reusable components - Software tools for evaluation or error analysis
Anthology ID:
N18-5001
Volume:
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Editors:
Yang Liu, Tim Paek, Manasi Patwardhan
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1–5
Language:
URL:
https://aclanthology.org/N18-5001
DOI:
10.18653/v1/N18-5001
Bibkey:
Cite (ACL):
Marc Schreiber, Bodo Kraft, and Albert Zündorf. 2018. NLP Lean Programming Framework: Developing NLP Applications More Effectively. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations, pages 1–5, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
NLP Lean Programming Framework: Developing NLP Applications More Effectively (Schreiber et al., NAACL 2018)
Copy Citation:
PDF:
https://aclanthology.org/N18-5001.pdf