As Figure 2 reveals, the learning curves of SeSAL stop early (on MUC7 after 12,800 tokens, on PENNBIOIE after 27,600 tokens) because at that point the whole corpus has been labeled exhaustively -either manually, or automatically.
we propose a semisupervised AL approach for sequence labeling where only highly uncertain subsequences are presented to human annotators, while all others in the selected sequences are automatically labeled.