Conference paper Open Access

WinoReg: A New Faster and More Accurate Metric of Hardness for Winograd Schemas

Nicos Isaak; Loizos Michael

The Winograd Schema Challenge (WSC), the task of resolving pronouns in certain carefully-structured sentences, has received considerable interest in the past few years as an alternative to the Turing Test. In our recent work we demonstrated the plausibility of
using commonsense knowledge, automatically acquired from raw text in English Wikipedia, towards computing a metric of hardness for a limited number of Winograd Schemas. In this work we present WinoReg, a new system to compute hardness of Winograd
Schemas, by training a Random Forest classier over a rich set of features identied in relevant WSC works in the literature. Our empirical study shows that this new system is considerably faster and more accurate compared to the system proposed in our earlier
work, making its use as part of other WSC-based systems feasible.

This work has received funding from the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No 739578 and under Grant Agreement No 823783 and the Government of the Republic of Cyprus through the Directorate General for European Programmes, Coordination and Development.
Files (433.2 kB)
Name Size
IsaakMichael_2020_winoreg_GCAI_pprint.pdf
md5:cef8cabc085808c3a2a17c265f615eb7
433.2 kB Download
11
8
views
downloads
Views 11
Downloads 8
Data volume 3.5 MB
Unique views 10
Unique downloads 8

Share

Cite as