Chinese Restaurant Process for cognate clustering: A threshold free approach
Table 3: Average B-cubed F-scores of different systems. The suffix “-CRP” stands for the CRP algorithm applied to Needleman-Wunsch (NW) and PMI word similarity methods.
['Dataset', 'LexStat', 'NW-CRP', 'PMI-CRP']
The CRP based PMI system performs better than LexStat on four datasets. The CRP algorithm performs slightly worse than the LexStat system on Austronesian and Indo-European language families by two points. The LexStat performs better than the PMI-CRP system only on the Ugric languages dataset. The LexStat system’s clustering threshold has been tuned on many smaller datasets whereas, the PMI-CRP does not require any tuning of the threshold and comes closer or performs better than the LexStat system. We also provide the average of B-cubed F-scores across different datasets. The results show that the PMI-CRP system is close to the performance of the LexStat system.