45 lines
1.1 KiB
Plaintext
45 lines
1.1 KiB
Plaintext
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## Natural Language Toolkit: sql.fcfg
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##
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## Deliberately naive string-based grammar for
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## deriving SQL queries from English
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##
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## Author: Ewan Klein <ewan@inf.ed.ac.uk>
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## URL: <http://nltk.sourceforge.net>
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## For license information, see LICENSE.TXT
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% start S
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S[SEM=(?np + WHERE + ?vp)] -> NP[SEM=?np] VP[SEM=?vp]
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VP[SEM=(?v + ?pp)] -> IV[SEM=?v] PP[SEM=?pp]
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VP[SEM=(?v + ?ap)] -> IV[SEM=?v] AP[SEM=?ap]
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VP[SEM=(?v + ?np)] -> TV[SEM=?v] NP[SEM=?np]
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VP[SEM=(?vp1 + ?c + ?vp2)] -> VP[SEM=?vp1] Conj[SEM=?c] VP[SEM=?vp2]
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NP[SEM=(?det + ?n)] -> Det[SEM=?det] N[SEM=?n]
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NP[SEM=(?n + ?pp)] -> N[SEM=?n] PP[SEM=?pp]
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NP[SEM=?n] -> N[SEM=?n] | CardN[SEM=?n]
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## NB Numbers in the Chat-80 database represent thousands.
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CardN[SEM='1000'] -> '1,000,000'
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PP[SEM=(?p + ?np)] -> P[SEM=?p] NP[SEM=?np]
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AP[SEM=?pp] -> A[SEM=?a] PP[SEM=?pp]
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NP[SEM='Country="greece"'] -> 'Greece'
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NP[SEM='Country="china"'] -> 'China'
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Det[SEM='SELECT'] -> 'Which' | 'What'
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Conj[SEM='AND'] -> 'and'
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N[SEM='City FROM city_table'] -> 'cities'
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N[SEM='Population'] -> 'populations'
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IV[SEM=''] -> 'are'
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TV[SEM=''] -> 'have'
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A -> 'located'
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P[SEM=''] -> 'in'
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P[SEM='>'] -> 'above'
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