The use of shared forests in tree adjoining grammar parsing
EACL '93 Proceedings of the sixth conference on European chapter of the Association for Computational Linguistics
A General Technique to Train Language Models on Language Models
Computational Linguistics
Computation of distances for regular and context-free probabilistic languages
Theoretical Computer Science
IWPT '09 Proceedings of the 11th International Conference on Parsing Technologies
Prefix probability for probabilistic synchronous context-free grammars
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Computation of infix probabilities for probabilistic context-free grammars
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Prefix probabilities for linear context-free rewriting systems
IWPT '11 Proceedings of the 12th International Conference on Parsing Technologies
| Hi-index | 0.00 |
The paradigm of parsing as intersection has been used throughout the literature to obtain elegant and general solutions to numerous problems involving grammars and automata. The paradigm has its origins in (Bar-Hillel et al., 1964), where a general construction was used to prove closure of context-free languages under intersection with regular languages. It was pointed out by (Lang, 1994) that such a construction isolates the parsing problem from the recognition problem. The latter can be solved by a reduction of the outcome of intersection. The paradigm has been extended in various ways, by considering more powerful formalisms, such as tree adjoining grammars (Vijay-Shanker and Weir, 1993), simple RCGs (Bertsch and Nederhof, 2001), tree grammars (Nederhof, 2009), and probabilistic extensions of grammatical formalisms (Nederhof and Satta, 2003). Different applications have been identified, such as computation of distances between languages (Nederhof and Satta, 2008), and parameter estimation of probabilistic models (Nederhof, 2005). The lecture will focus on another application, namely the computation of prefix probabilities (Nederhof and Satta, 2011c) and infix probabilities (Nederhof and Satta, 2011a) and will address novel generalisations to linear context-free rewriting systems (Nederhof and Satta, 2011b).