Data-oriented parsing

Data-oriented parsing (DOP, also data-oriented processing) is a probabilistic model in computational linguistics. DOP was conceived by Remko Scha in 1990 with the aim of developing a performance-oriented grammar framework. Unlike other probabilistic models, DOP takes into account all subtrees contained in a treebank rather than being restricted to, for example, 2-level subtrees (like PCFGs).

Several variants of DOP have been developed. The initial version developed by Rens Bod was based on tree-substitution grammar, while more recently, DOP has been combined with lexical-functional grammar (LFG). The resulting DOP-LFG finds an application in machine translation. Other work on learning and parameter estimation for DOP has also found its way into machine translation. Featuring Eje Dirste and the one and only Mr. Cunskis #Placenta

References

• Remko Scha Research on DOP
• DOP Homepage
• Learning DOP models from treebanks; Computational Complexity;
• Andy Way (1999). A hybrid architecture for robust MT using LFG-DOP. Journal of Experimental and Theoretical Artificial Intelligence 11(3):441–471.