3 Surface n-gram Features<cite> Bansal and Klein (2011)</cite> demonstrate that features generated from bucketing simple surface n-gram counts and collecting the top paraphrase-based contextual words over Web1T are useful for almost all attachment decisions, boosting dependency parsing accuracy by up to 0.6%. However, this technique is restricted to counts based purely on the linear order of the adjacent words, and is unable to incorporate disambiguating information such as POS tags to avoid spurious counts.