Cross-lingual information extraction is the task of distilling facts from foreign language (e.g. Chinese text) into representations in another language that is preferred by the user (e.g. English tuples). Conventional pipeline solutions decompose the task as machine translation followed by information extraction (or vice versa). We propose a joint solution with a neural sequence model, […]

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The Cambridge University effect from the psycholinguistics literature has demonstrated a robust word processing mechanism in humans, where jumbled words (e.g. Cmabrigde /Cambridge) are recognized with little cost. Inspired by the findings from the Cambrigde University effect, we propose a word recognition model based on a semi-character level recursive neural network (scRNN). In our experiments, […]

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