Demonstrating Par4Sem - A Semantic Writing Aid with Adaptive Paraphrasing

Seid Muhie Yimam, Chris Biemann


Abstract
In this paper, we present Par4Sem, a semantic writing aid tool based on adaptive paraphrasing. Unlike many annotation tools that are primarily used to collect training examples, Par4Sem is integrated into a real word application, in this case a writing aid tool, in order to collect training examples from usage data. Par4Sem is a tool, which supports an adaptive, iterative, and interactive process where the underlying machine learning models are updated for each iteration using new training examples from usage data. After motivating the use of ever-learning tools in NLP applications, we evaluate Par4Sem by adopting it to a text simplification task through mere usage.
Anthology ID:
D18-2009
Volume:
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
Month:
November
Year:
2018
Address:
Brussels, Belgium
Editors:
Eduardo Blanco, Wei Lu
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
48–53
Language:
URL:
https://aclanthology.org/D18-2009
DOI:
10.18653/v1/D18-2009
Bibkey:
Cite (ACL):
Seid Muhie Yimam and Chris Biemann. 2018. Demonstrating Par4Sem - A Semantic Writing Aid with Adaptive Paraphrasing. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 48–53, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
Demonstrating Par4Sem - A Semantic Writing Aid with Adaptive Paraphrasing (Yimam & Biemann, EMNLP 2018)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-1/D18-2009.pdf