We consider what tagging models are most appropriate as front ends for probabilistic context-free grammar parsers. In particular, we ask if using a "multiple tagger", a tagger that returns more than one tag, improves parsing performance. Our conclusion is somewhat surprising: single-tag Markov-mode
Evaluating GLR parsing algorithms
โ Scribed by Adrian Johnstone; Elizabeth Scott; Giorgios Economopoulos
- Publisher
- Elsevier Science
- Year
- 2006
- Tongue
- English
- Weight
- 495 KB
- Volume
- 61
- Category
- Article
- ISSN
- 0167-6423
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โฆ Synopsis
We describe the behaviour of three variants of GLR parsing: (i) Farshi's original correction to Tomita's non-general algorithm; (ii) the Right Nulled GLR algorithm which provides a more efficient generalisation of Tomita and (iii) the Binary Right Nulled GLR algorithm, on three types of LR table. We present a guide to the parse-time behaviour of these algorithms which illustrates the inefficiencies in conventional Farshi-style GLR parsing. We also describe the tool GTB (Grammar Tool Box) which provides a platform for comparative studies of parsing algorithms; and use GTB to exercise the three GLR algorithms running with LR(0), SLR(1) and LR(1) tables for ANSI-C, ISO-Pascal and IBM VS-COBOL. We give results showing the size of the structures constructed by these parsers and the amount of searching required during the parse, which abstracts their runtime.
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