As shown in Table 3, reducing the dictionary by filtering rare words (with count<= d) has not been a promising track to follow for accomplishing the task with as little information as possible.
by introducing a lexicon acquisition step, we achieve a tagging accuracy of 90.6% for the 24K test data with no prior open-class lexicon, provided with only a minimal lexicon of closed-class items (about 0.6% of the full lexicon), as high as  the best previous performance of 90.4 given a full lexicon (CRF/CE with d = 1) 12 .