Syntactic Dependency Representations in Neural Relation Classification

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May 28, 2018
Farhad Nooralahzadeh, Lilja Øvrelid
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We investigate the use of different syntactic dependency representations in a neural relation classification task and compare the CoNLL, Stanford Basic and Universal Dependencies schemes. We further compare with a syntax-agnostic approach and perform an error analysis in order to gain a better understanding of the results.

* arXiv admin note: text overlap with arXiv:1804.08887  
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