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Extra info for Analyses of Decommissioning the Reference PWR Power Station Vol 2 [appendices]

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4. 5. 6. 7. 8. 9. Geoffrey Leech and Roger Garside o u t " by the use of features), rather than on a more powerful formalism such as Generalized Phrase Structure G r a m m a r . T h e Lancaster-Oslo/Bergen C o r p u s (LOB Corpus) is described in Johansson et al. (1978). Jelinek (1985) gives some of the background of this research, which uses probabilistic analyses of large corpora to build language models for speech-to-text systems: in particular, for the Tangora automatic dictation machine developed by IBM.

In fact, the treebankers who worked on skeleton parsing were not novices: some of them had already had experience of parsing under the "steeper grammar" scheme, and two or three of them had degrees in subjects related to languages and linguistics. 13 In spite of differences of opinion about the extent of background knowledge or theory a treebanker would use, it was agreed, and subsequently confirmed in practice, that (a) skeleton parsing should remain simple, facilitating speed of input; (b) parsing practice should be governed by (i) a limited use of guidelines (i.

Probabilistic rules and lexicons We have extracted the systemic functional grammatical information from the Polytechnic of Wales and ARK corpora into probabilistic lexicons, sets of probabilistic context-free rules, and a probabilistic Recursive Transition Network (which is described below). The lexicon is collected Probabilistic parsing in the C O M M U N A L project 39 by extracting all the combinations of words and word tags from the corpora, and keeping a count of multiple copies. Some lexical items which would be analysed as part of a proper name cluster in the A R K corpus are given below as examples.

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