An Empirical Comparison of Parsing Methods for Stanford Dependencies
Table 7: Incorporating distributional word representations into Basic SD parsing. Numerals in the leftmost column refer to rows in Table 1.
['[EMPTY]', 'Parser', 'PTB §22 UAS', 'PTB §22 LAS', 'PTB §23 UAS', 'PTB §23 LAS', 'Speed (tokens/s.)']
Both Full TurboParser and Standard TurboParser get improvement from the cluster-based features. We compare to the Stanford recursive neural network parser. The Full TurboParser matches the performance of the Stanford RNN model with around 3 times the speed, and the Standard TurboParser is slightly behind the Stanford RNN model but may provides another reasonable accuracy/speed trade-off here.