Proceedings of the Workshop on Computational Semantics beyond Events and Roles

Eduardo Blanco, Roser Morante (Editors)


Anthology ID:
W18-13
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Venues:
NAACL | SemBEaR | WS
SIG:
Publisher:
Association for Computational Linguistics
URL:
https://aclanthology.org/W18-13
DOI:
10.18653/v1/W18-13
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PDF:
https://aclanthology.org/W18-13.pdf

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Proceedings of the Workshop on Computational Semantics beyond Events and Roles
Eduardo Blanco | Roser Morante

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Using Hedge Detection to Improve Committed Belief Tagging
Morgan Ulinski | Seth Benjamin | Julia Hirschberg

We describe a novel method for identifying hedge terms using a set of manually constructed rules. We present experiments adding hedge features to a committed belief system to improve classification. We compare performance of this system (a) without hedging features, (b) with dictionary-based features, and (c) with rule-based features. We find that using hedge features improves performance of the committed belief system, particularly in identifying instances of non-committed belief and reported belief.

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Detecting Sarcasm is Extremely Easy ;-)
Natalie Parde | Rodney Nielsen

Detecting sarcasm in text is a particularly challenging problem in computational semantics, and its solution may vary across different types of text. We analyze the performance of a domain-general sarcasm detection system on datasets from two very different domains : Twitter, and Amazon product reviews. We categorize the errors that we identify with each, and make recommendations for addressing these issues in NLP systems in the future.