Better call Saul: Flexible Programming for Learning and Inference in NLP

COLING 2016 Parisa KordjamshidiDaniel KhashabiChristos ChristodoulopoulosBhargav MangipudiSameer SinghDan Roth

We present a novel way for designing complex joint inference and learning models using Saul (Kordjamshidi et al., 2015), a recently-introduced declarative learning-based programming language (DeLBP). We enrich Saul with components that are necessary for a broad range of learning based Natural Language Processing tasks at various levels of granularity... (read more)

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