SHOMA at Parseme Shared Task on Automatic Identification of VMWEs: Neural Multiword Expression Tagging with High Generalisation
Table 1: Validation results for the data of shared task edition 1.1.
['[EMPTY]', 'Model', 'Token-based P', 'Token-based R', 'Token-based F1', 'MWE-based P', 'MWE-based R', 'MWE-based F1']
We see consistent improvement compared to the baselines (CRF and Turian) in all languages except for Persian (Fa). The good performance of the baselines for Persian can be attributed to the fact that in the Persian dataset, MWEs are all LVCs which follow a rigid structure. They are usually constructed from a small number of verbs plus nouns. Also, the proportion of seen MWE types is comparatively high. This makes their detection fairly easy for a pattern-based model.