NLPwin – an introduction
Lucy Vanderwende · 2015
Since we knew that we were developing NLPwin in part to support a grammar checker, the NLPwin grammar is designed to be broad-coverage (i.e., not domain-specific) and robust, in particular, robust to grammar errors. While most grammars are learned from data annotated on the PennTreeBank (Marcus et al., 1993), it is interesting to consider that such grammars may not be able to parse ungrammatical or fragmented grammar, since those grammars have no training data for such input. The NLPwin grammar produces a parse for any input and if no spanning parse can be assigned, it creates a “fitted” parse, combining the largest constituents that it was able to construct.