In this work we choose shift-reduce dependency parsing for its simplicity and efficiency.
we make the following contributions: • we develop a baseline shift-reduce dependency parser using the less popular, but classical, "arc-standard" style (Section 2), and achieve similar state-of-the-art performance with the the dominant but complicated "arceager" style of Nivre and Scholz (2004); • we propose bilingual features based on wordalignment information to prefer "target-side contiguity" in resolving shift-reduce conflicts (Section 3); • we verify empirically that shift-reduce conflicts are the major source of errors, and correct shift-reduce decisions strongly correlate with the above bilingual contiguity conditions even with automatic alignments (Section 5.3); • finally, with just three bilingual features, we improve dependency parsing accuracy by 0.6% for both English and Chinese over the state-of-the-art baseline with negligible (∼6%) efficiency overhead (Section 5.4).