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We present an approach to unsupervised partial parsing: the identification of low-level constituents (which we dub clumps) in unannotated text. We begin by showing that CCLParser (Seginer 2007), an unsupervised parsing model, is particularly adept at identifying clumps, and that, surprisingly, building a simple right-branching structure above its clumps actually outperforms the full parser itself,...
Automatically identifying the arguments of discourse connectives (e.g., and, because, however) is an important part of modeling discourse structure. Previous work used a single, general classifier for different connectives; however, connectives differ in their distribution and behavior, so conflating them this way loses discriminative power. Here, we show that using models for specific connectives...
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