We use a generative history-based model to predict the most likely derivation of a dependency parse. Our probabilistic model is based on Incremental Sigmoid Belief Networks, a rec...
We present a two-stage multilingual dependency parsing system submitted to the Multilingual Track of CoNLL-2007. The parser first identifies dependencies using a deterministic p...
We investigate a series of targeted modifications to a data-driven dependency parser of German and show that these can be highly effective even for a relatively well studied langu...
Parsing plays an important role in semantic role labeling (SRL) because most SRL systems infer semantic relations from 1-best parses. Therefore, parsing errors inevitably lead to ...
This paper introduces and analyzes a battery of inference models for the problem of semantic role labeling: one based on constraint satisfaction, and several strategies that model...