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Identifying Domain Adjacent Instances for Semantic Parsers

James Ferguson
Edward Li
Edgar Gonzàlez Pellicer
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

Abstract

When the semantics of an input are not representable in a sematic parser’s output schema, parsing will inevitably fail. Detection of these instances is commonly treated as an out-of domain classification problem. However, there is also a more subtle scenario in which the test data is drawn from the same domain. In addition to formalizing this problem of domain-adjacency, we present a comparison of various baselines that could be used to solve it. We also propose a new simple sentence representation that emphasizes words which are unexpected. This approach improves the performance of a downstream semantic parser run on in-domain and domain-adjacent instances.