Semantic Specialisation of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints
Table 5: SimLex-999 performance. Tying the SimLex languages into bilingual vector spaces with 16 different languages. The first number in each row represents monolingual specialisation. All but two of the bilingual spaces improved over these baselines. The EN-FR vectors set a new high score of 0.754 on the original (English) SimLex-999.
['[EMPTY]', '[BOLD] Mono.  [BOLD] Spec.', 'SimLex Languages  [BOLD] EN', 'SimLex Languages  [BOLD] DE', 'SimLex Languages  [BOLD] IT', 'SimLex Languages  [BOLD] RU', 'PPDB available  [BOLD] NL', 'PPDB available  [BOLD] FR', 'PPDB available  [BOLD] ES', 'PPDB available  [BOLD] PT', 'PPDB available  [BOLD] PL', 'PPDB available  [BOLD] BG', 'No PPDB available  [BOLD] HR', 'No PPDB available  [BOLD] HE', 'No PPDB available  [BOLD] GA', 'No PPDB available  [BOLD] VI', 'No PPDB available  [BOLD] FA', 'No PPDB available  [BOLD] SV']
4.1). Bilingual specialisation substantially improves over monolingual specialisation for all language pairs. This indicates that our improvements are language independent to a large extent.