TakeLab at SemEval-2018 Task12: Argument Reasoning Comprehension with Skip-Thought Vectors (CROSBI ID 662796)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Brassard, Ana ; Kuculo, Tin ; Boltužić, Filip ; Šnajder, Jan
engleski
TakeLab at SemEval-2018 Task12: Argument Reasoning Comprehension with Skip-Thought Vectors
This paper describes our system for the SemEval-2018 Task 12: Argument Reasoning Comprehension Task. We utilize skip-thought vectors, sentence-level distributional vectors inspired by the popular word embeddings and the skip-gram model. We encode preprocessed sentences from the dataset into vectors, then perform a binary supervised classification of the warrant that justifies the use of the reason as support for the claim. We explore a few variations of the model, reaching 54.1% accuracy on the test set, which placed us 16th out of 22 teams participating in the task.
Argumentation mining ; warrant detection ; online discussions ; support vector machines
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Podaci o prilogu
1133-1136.
2018.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of The 12th International Workshop on Semantic Evaluation
New Orleans (LA): Association for Computational Linguistics (ACL)
Podaci o skupu
12th International Workshop on Semantic Evaluation (SemEval-2018)
poster
06.06.2018-06.06.2018
New Orleans (LA), Sjedinjene Američke Države