Learning Joint Semantic Parsers from Disjoint Data
Table 3: Frame identification accuracy on the FN 1.5 test set. Ambiguous evaluates only on lexical units having more than one possible frames. † denotes joint frame and argument identification, and bold font indicates best performance.141414Our comparison to Hermann et al. (2014) is based on their updated version: http://www.aclweb.org/anthology/P/P14/P14-1136v2.pdf. Ambiguous frame identification results by Yang and Mitchell (2017) and Hartmann et al. (2017) are 75.7 and 73.8. Their ambiguous lexical unit sets are different from the one extracted from the official frame directory, and thus the results are not comparable to those in Table 3.
['[BOLD] Model', '[BOLD] All', '[BOLD] Ambiguous']
Hermann et al. The Ambiguous setting compares lexical units with more than one possible frames. Our approach improves over all previous models under both settings, demonstrating a clear benefit from joint learning. Our comparison to Hermann et al.