We treat shallow parsing as a sequence label task, and a sentence f can have many possible different chunk label sequences.
in theory, the conditional probability of a target translation e conditioned on the source sentence f is given by taking the chunk label sequences as a latent variable c: In practice, we only take the best chunk label sequenceĉ got byĉ Then we can ignore the conditional probability p(ĉ|f ) as it holds the same value for each translation, and get: We formalize our model as a weighted SCFG.