PetSelectiveUnpacking

Overview

The ambiguity packing mechanism has been proved to be crucial for better efficiency in constraint-based parsing. In the PET system, bi-directional subsumption-based ambiguity packing ([Oepen & Carroll, 2000]) is implemented. With this packing mechanism, parsing is divided into two separate phases: the parse forest creation phase, and the unpacking phase. This first phase creates the packed representation of the parse forest, while the later phase recreates the parsing results from the packed representation. With ambiguity packing, the cost (time and space) of creating the parse forest is largely reduced. Unfortunately, the task of extracting the parsing results from the packed forest is non-trivial when subsumption-based packing is used. In the earlier implementation of PET, the exhaustive unpacking is used, which can easily ran out of edge limit for highly ambiguous sentences.

In [Carroll & Oepen, 2005], a selective unpacking algorithm was proposed which, in combination with the parse selection model, can efficiently extract a specific number of (best) readings from the packed parse forest. The key idea is that the most expensive unification operations are postponed as much as possible and only performed on the best hypotheses. The initial algorithm has been implemented for LKB, and now is also available for PET (still in SVN as of 2006-10-20) with some extensions.

How to use it?

As of 2006-10-20, you will need the latest SVN version of the PET for selective unpacking.

You will also need a parse selection model (a `.mem' file). PET now supports two different `.mem' file formats. Both should work with the selective unpacking. But you will need the new format for grand-parenting features.

Here is a sample session, where only the best 10 analyses are unpacked.

[yzhang@takeshi erg.sep-06]$ cheap -packing=15 -nsolutions=10 english.grm
reading `pet/english.set'... including `pet/common.set'... `pet/global.set'...
loading `english.grm' (LinGO (27-Sept-06)) reading ME model `jhpstg.mem'... [115045 features]
68443 types in 17 s
kim saw a mouse in the hotel
(1) `kim saw a mouse in the hotel' [0] --- 3 (0.22|0.25s) <30:236> (1339.0K) [0.2s]
kim saw a mouse in the hotel in the hotel in the hotel
(2) `kim saw a mouse in the hotel in the hotel in the hotel' [0] --- 10 (0.68|0.77s) <48:487> (3094.2K) [1.0s]

Note that -nsolutions must be set to be >0. Otherwise exhaustive unpacking will be used.

References

• [Oepen & Carroll, 2000]. Ambiguity packing in constraint-based parsing --- practical results. In Proceedings of the 1st Conference of the North American Chapter of the ACL, 162--169. Seattle, WA.

• [Carroll & Oepen, 2005]. High efficiency realization for a wide-coverage unification grammar. Proceedings of the Second International Joint Conference on Natural Language Processing (IJCNLP05), 165--176. Jeju Island, Korea.