ETHAN at SemEval-2020 Task 5: Modelling Causal Reasoning in Language Using Neuro-symbolic Cloud Computing

Len Yabloko


Abstract
I present ETHAN: Experimental Testing of Hybrid AI Node implemented entirely on free cloud computing infrastructure. The ultimate goal of this research is to create modular reusable hybrid neuro-symbolic architecture for Artificial Intelligence. As a test case I model natural language comprehension of causal relations from open domain text corpus that combines semi-supervised language model (Huggingface Transformers) with constituency and dependency parsers (Allen Institute for Artificial Intelligence.)
Anthology ID:
2020.semeval-1.83
Volume:
Proceedings of the Fourteenth Workshop on Semantic Evaluation
Month:
December
Year:
2020
Address:
Barcelona (online)
Editors:
Aurelie Herbelot, Xiaodan Zhu, Alexis Palmer, Nathan Schneider, Jonathan May, Ekaterina Shutova
Venue:
SemEval
SIG:
SIGLEX
Publisher:
International Committee for Computational Linguistics
Note:
Pages:
645–652
Language:
URL:
https://aclanthology.org/2020.semeval-1.83
DOI:
10.18653/v1/2020.semeval-1.83
Bibkey:
Cite (ACL):
Len Yabloko. 2020. ETHAN at SemEval-2020 Task 5: Modelling Causal Reasoning in Language Using Neuro-symbolic Cloud Computing. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 645–652, Barcelona (online). International Committee for Computational Linguistics.
Cite (Informal):
ETHAN at SemEval-2020 Task 5: Modelling Causal Reasoning in Language Using Neuro-symbolic Cloud Computing (Yabloko, SemEval 2020)
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PDF:
https://aclanthology.org/2020.semeval-1.83.pdf