Clippers Tuesday: Reid Fu on Neural Hypertagging

Hypertagging, or supertagging for realization, is the process of assigning CCG tags to predicates. Previous work has shown that it significantly increases realization speed and quality by reducing the search space of the realizer. This project seeks to improve on the current OpenCCG hypertagger, which uses a two-stage maximum entropy algorithm and reaches a dev accuracy of 95.1%. In this talk, I will present the results of various experiments using an LSTM hypertagger with different logical form linearization schemes. The performance with a pre-order linearization scheme is slightly under that of the current OpenCCG hypertagger, but the oracle linearization suggests that with a more English-like linearization, hypertagging with an LSTM is a promising way forward.