A Chunk-Driven Bootstrapping Approach to Extracting Translation Patterns

Abstract. We present a linguistically-motivated sub-sentential alignment system that extends the intersected IBM Model 4 word alignments. The alignment system is chunk-driven and requires only shallow linguistic processing tools for the source and the target languages, i.e. part-ofspeech taggers and chunkers. We conceive the sub-sentential aligner as a cascaded model consisting of two phases. In the first phase, anchor chunks are linked based on the intersected word alignments and syntactic similarity. In the second phase, we use a bootstrapping approach to extract more complex translation patterns. The results show an overall AER reduction and competitive F-Measures in comparison to the commonly used symmetrized IBM Model 4 predictions (intersection, union and grow-diag-final) on six different text types for English-Dutch. More in particular, in comparison with the intersected word alignments, the proposed method improves recall, without sacrificing precision. Moreover, the system is ...

• Type: Journal
• Year: 2010
• Where: CICLING
• Authors: Lieve Macken, Walter Daelemans
• Keywords: CICLING 2010, IBM Model, Intersected Word Alignments, Natural Language Processing, Word Alignments