n-Best Parsing Revisited

We derive and implement an algorithm similar to (Huang and Chiang, 2005) for finding the n best derivations in a weighted hypergraph. We prove the correctness and termination of the algorithm and we show experimental results concerning its runtime. Our work is different from the aforementioned one in the following respects: we consider labeled hypergraphs, allowing for tree-based language models (Maletti and Satta, 2009); we specifically handle the case of cyclic hypergraphs; we admit structured weight domains, allowing for multiple features to be processed; we use the paradigm of functional programming together with lazy evaluation, achieving concise algorithmic descriptions.