updates
This commit is contained in:
Iliyan Angelov
376
Backend/venv/lib/python3.12/site-packages/nltk/test/ccg.doctest
Normal file
376
Backend/venv/lib/python3.12/site-packages/nltk/test/ccg.doctest
Normal file
@@ -0,0 +1,376 @@
|
||||
.. Copyright (C) 2001-2025 NLTK Project
|
||||
.. For license information, see LICENSE.TXT
|
||||
|
||||
==============================
|
||||
Combinatory Categorial Grammar
|
||||
==============================
|
||||
|
||||
Relative Clauses
|
||||
----------------
|
||||
|
||||
>>> from nltk.ccg import chart, lexicon
|
||||
|
||||
Construct a lexicon:
|
||||
|
||||
>>> lex = lexicon.fromstring('''
|
||||
... :- S, NP, N, VP
|
||||
...
|
||||
... Det :: NP/N
|
||||
... Pro :: NP
|
||||
... Modal :: S\\NP/VP
|
||||
...
|
||||
... TV :: VP/NP
|
||||
... DTV :: TV/NP
|
||||
...
|
||||
... the => Det
|
||||
...
|
||||
... that => Det
|
||||
... that => NP
|
||||
...
|
||||
... I => Pro
|
||||
... you => Pro
|
||||
... we => Pro
|
||||
...
|
||||
... chef => N
|
||||
... cake => N
|
||||
... children => N
|
||||
... dough => N
|
||||
...
|
||||
... will => Modal
|
||||
... should => Modal
|
||||
... might => Modal
|
||||
... must => Modal
|
||||
...
|
||||
... and => var\\.,var/.,var
|
||||
...
|
||||
... to => VP[to]/VP
|
||||
...
|
||||
... without => (VP\\VP)/VP[ing]
|
||||
...
|
||||
... be => TV
|
||||
... cook => TV
|
||||
... eat => TV
|
||||
...
|
||||
... cooking => VP[ing]/NP
|
||||
...
|
||||
... give => DTV
|
||||
...
|
||||
... is => (S\\NP)/NP
|
||||
... prefer => (S\\NP)/NP
|
||||
...
|
||||
... which => (N\\N)/(S/NP)
|
||||
...
|
||||
... persuade => (VP/VP[to])/NP
|
||||
... ''')
|
||||
|
||||
>>> parser = chart.CCGChartParser(lex, chart.DefaultRuleSet)
|
||||
>>> for parse in parser.parse("you prefer that cake".split()):
|
||||
... chart.printCCGDerivation(parse)
|
||||
... break
|
||||
...
|
||||
you prefer that cake
|
||||
NP ((S\NP)/NP) (NP/N) N
|
||||
-------------->
|
||||
NP
|
||||
--------------------------->
|
||||
(S\NP)
|
||||
--------------------------------<
|
||||
S
|
||||
|
||||
>>> for parse in parser.parse("that is the cake which you prefer".split()):
|
||||
... chart.printCCGDerivation(parse)
|
||||
... break
|
||||
...
|
||||
that is the cake which you prefer
|
||||
NP ((S\NP)/NP) (NP/N) N ((N\N)/(S/NP)) NP ((S\NP)/NP)
|
||||
----->T
|
||||
(S/(S\NP))
|
||||
------------------>B
|
||||
(S/NP)
|
||||
---------------------------------->
|
||||
(N\N)
|
||||
----------------------------------------<
|
||||
N
|
||||
------------------------------------------------>
|
||||
NP
|
||||
------------------------------------------------------------->
|
||||
(S\NP)
|
||||
-------------------------------------------------------------------<
|
||||
S
|
||||
|
||||
|
||||
Some other sentences to try:
|
||||
"that is the cake which we will persuade the chef to cook"
|
||||
"that is the cake which we will persuade the chef to give the children"
|
||||
|
||||
>>> sent = "that is the dough which you will eat without cooking".split()
|
||||
>>> nosub_parser = chart.CCGChartParser(lex, chart.ApplicationRuleSet +
|
||||
... chart.CompositionRuleSet + chart.TypeRaiseRuleSet)
|
||||
|
||||
Without Substitution (no output)
|
||||
|
||||
>>> for parse in nosub_parser.parse(sent):
|
||||
... chart.printCCGDerivation(parse)
|
||||
|
||||
With Substitution:
|
||||
|
||||
>>> for parse in parser.parse(sent):
|
||||
... chart.printCCGDerivation(parse)
|
||||
... break
|
||||
...
|
||||
that is the dough which you will eat without cooking
|
||||
NP ((S\NP)/NP) (NP/N) N ((N\N)/(S/NP)) NP ((S\NP)/VP) (VP/NP) ((VP\VP)/VP['ing']) (VP['ing']/NP)
|
||||
----->T
|
||||
(S/(S\NP))
|
||||
------------------------------------->B
|
||||
((VP\VP)/NP)
|
||||
----------------------------------------------<Sx
|
||||
(VP/NP)
|
||||
----------------------------------------------------------->B
|
||||
((S\NP)/NP)
|
||||
---------------------------------------------------------------->B
|
||||
(S/NP)
|
||||
-------------------------------------------------------------------------------->
|
||||
(N\N)
|
||||
---------------------------------------------------------------------------------------<
|
||||
N
|
||||
----------------------------------------------------------------------------------------------->
|
||||
NP
|
||||
------------------------------------------------------------------------------------------------------------>
|
||||
(S\NP)
|
||||
------------------------------------------------------------------------------------------------------------------<
|
||||
S
|
||||
|
||||
|
||||
Conjunction
|
||||
-----------
|
||||
|
||||
>>> from nltk.ccg.chart import CCGChartParser, ApplicationRuleSet, CompositionRuleSet
|
||||
>>> from nltk.ccg.chart import SubstitutionRuleSet, TypeRaiseRuleSet, printCCGDerivation
|
||||
>>> from nltk.ccg import lexicon
|
||||
|
||||
Lexicons for the tests:
|
||||
|
||||
>>> test1_lex = '''
|
||||
... :- S,N,NP,VP
|
||||
... I => NP
|
||||
... you => NP
|
||||
... will => S\\NP/VP
|
||||
... cook => VP/NP
|
||||
... which => (N\\N)/(S/NP)
|
||||
... and => var\\.,var/.,var
|
||||
... might => S\\NP/VP
|
||||
... eat => VP/NP
|
||||
... the => NP/N
|
||||
... mushrooms => N
|
||||
... parsnips => N'''
|
||||
>>> test2_lex = '''
|
||||
... :- N, S, NP, VP
|
||||
... articles => N
|
||||
... the => NP/N
|
||||
... and => var\\.,var/.,var
|
||||
... which => (N\\N)/(S/NP)
|
||||
... I => NP
|
||||
... anyone => NP
|
||||
... will => (S/VP)\\NP
|
||||
... file => VP/NP
|
||||
... without => (VP\\VP)/VP[ing]
|
||||
... forget => VP/NP
|
||||
... reading => VP[ing]/NP
|
||||
... '''
|
||||
|
||||
Tests handling of conjunctions.
|
||||
Note that while the two derivations are different, they are semantically equivalent.
|
||||
|
||||
>>> lex = lexicon.fromstring(test1_lex)
|
||||
>>> parser = CCGChartParser(lex, ApplicationRuleSet + CompositionRuleSet + SubstitutionRuleSet)
|
||||
>>> for parse in parser.parse("I will cook and might eat the mushrooms and parsnips".split()):
|
||||
... printCCGDerivation(parse)
|
||||
I will cook and might eat the mushrooms and parsnips
|
||||
NP ((S\NP)/VP) (VP/NP) ((_var0\.,_var0)/.,_var0) ((S\NP)/VP) (VP/NP) (NP/N) N ((_var0\.,_var0)/.,_var0) N
|
||||
---------------------->B
|
||||
((S\NP)/NP)
|
||||
---------------------->B
|
||||
((S\NP)/NP)
|
||||
------------------------------------------------->
|
||||
(((S\NP)/NP)\.,((S\NP)/NP))
|
||||
-----------------------------------------------------------------------<
|
||||
((S\NP)/NP)
|
||||
------------------------------------->
|
||||
(N\.,N)
|
||||
------------------------------------------------<
|
||||
N
|
||||
-------------------------------------------------------->
|
||||
NP
|
||||
------------------------------------------------------------------------------------------------------------------------------->
|
||||
(S\NP)
|
||||
-----------------------------------------------------------------------------------------------------------------------------------<
|
||||
S
|
||||
I will cook and might eat the mushrooms and parsnips
|
||||
NP ((S\NP)/VP) (VP/NP) ((_var0\.,_var0)/.,_var0) ((S\NP)/VP) (VP/NP) (NP/N) N ((_var0\.,_var0)/.,_var0) N
|
||||
---------------------->B
|
||||
((S\NP)/NP)
|
||||
---------------------->B
|
||||
((S\NP)/NP)
|
||||
------------------------------------------------->
|
||||
(((S\NP)/NP)\.,((S\NP)/NP))
|
||||
-----------------------------------------------------------------------<
|
||||
((S\NP)/NP)
|
||||
------------------------------------------------------------------------------->B
|
||||
((S\NP)/N)
|
||||
------------------------------------->
|
||||
(N\.,N)
|
||||
------------------------------------------------<
|
||||
N
|
||||
------------------------------------------------------------------------------------------------------------------------------->
|
||||
(S\NP)
|
||||
-----------------------------------------------------------------------------------------------------------------------------------<
|
||||
S
|
||||
|
||||
|
||||
Tests handling subject extraction.
|
||||
Interesting to point that the two parses are clearly semantically different.
|
||||
|
||||
>>> lex = lexicon.fromstring(test2_lex)
|
||||
>>> parser = CCGChartParser(lex, ApplicationRuleSet + CompositionRuleSet + SubstitutionRuleSet)
|
||||
>>> for parse in parser.parse("articles which I will file and forget without reading".split()):
|
||||
... printCCGDerivation(parse)
|
||||
articles which I will file and forget without reading
|
||||
N ((N\N)/(S/NP)) NP ((S/VP)\NP) (VP/NP) ((_var0\.,_var0)/.,_var0) (VP/NP) ((VP\VP)/VP['ing']) (VP['ing']/NP)
|
||||
-----------------<
|
||||
(S/VP)
|
||||
------------------------------------->B
|
||||
((VP\VP)/NP)
|
||||
----------------------------------------------<Sx
|
||||
(VP/NP)
|
||||
------------------------------------------------------------------------->
|
||||
((VP/NP)\.,(VP/NP))
|
||||
----------------------------------------------------------------------------------<
|
||||
(VP/NP)
|
||||
--------------------------------------------------------------------------------------------------->B
|
||||
(S/NP)
|
||||
------------------------------------------------------------------------------------------------------------------->
|
||||
(N\N)
|
||||
-----------------------------------------------------------------------------------------------------------------------------<
|
||||
N
|
||||
articles which I will file and forget without reading
|
||||
N ((N\N)/(S/NP)) NP ((S/VP)\NP) (VP/NP) ((_var0\.,_var0)/.,_var0) (VP/NP) ((VP\VP)/VP['ing']) (VP['ing']/NP)
|
||||
-----------------<
|
||||
(S/VP)
|
||||
------------------------------------>
|
||||
((VP/NP)\.,(VP/NP))
|
||||
---------------------------------------------<
|
||||
(VP/NP)
|
||||
------------------------------------->B
|
||||
((VP\VP)/NP)
|
||||
----------------------------------------------------------------------------------<Sx
|
||||
(VP/NP)
|
||||
--------------------------------------------------------------------------------------------------->B
|
||||
(S/NP)
|
||||
------------------------------------------------------------------------------------------------------------------->
|
||||
(N\N)
|
||||
-----------------------------------------------------------------------------------------------------------------------------<
|
||||
N
|
||||
|
||||
|
||||
Unicode support
|
||||
---------------
|
||||
|
||||
Unicode words are supported.
|
||||
|
||||
>>> from nltk.ccg import chart, lexicon
|
||||
|
||||
Lexicons for the tests:
|
||||
|
||||
>>> lex = lexicon.fromstring('''
|
||||
... :- S, N, NP, PP
|
||||
...
|
||||
... AdjI :: N\\N
|
||||
... AdjD :: N/N
|
||||
... AdvD :: S/S
|
||||
... AdvI :: S\\S
|
||||
... Det :: NP/N
|
||||
... PrepNPCompl :: PP/NP
|
||||
... PrepNAdjN :: S\\S/N
|
||||
... PrepNAdjNP :: S\\S/NP
|
||||
... VPNP :: S\\NP/NP
|
||||
... VPPP :: S\\NP/PP
|
||||
... VPser :: S\\NP/AdjI
|
||||
...
|
||||
... auto => N
|
||||
... bebidas => N
|
||||
... cine => N
|
||||
... ley => N
|
||||
... libro => N
|
||||
... ministro => N
|
||||
... panadería => N
|
||||
... presidente => N
|
||||
... super => N
|
||||
...
|
||||
... el => Det
|
||||
... la => Det
|
||||
... las => Det
|
||||
... un => Det
|
||||
...
|
||||
... Ana => NP
|
||||
... Pablo => NP
|
||||
...
|
||||
... y => var\\.,var/.,var
|
||||
...
|
||||
... pero => (S/NP)\\(S/NP)/(S/NP)
|
||||
...
|
||||
... anunció => VPNP
|
||||
... compró => VPNP
|
||||
... cree => S\\NP/S[dep]
|
||||
... desmintió => VPNP
|
||||
... lee => VPNP
|
||||
... fueron => VPPP
|
||||
...
|
||||
... es => VPser
|
||||
...
|
||||
... interesante => AdjD
|
||||
... interesante => AdjI
|
||||
... nueva => AdjD
|
||||
... nueva => AdjI
|
||||
...
|
||||
... a => PrepNPCompl
|
||||
... en => PrepNAdjN
|
||||
... en => PrepNAdjNP
|
||||
...
|
||||
... ayer => AdvI
|
||||
...
|
||||
... que => (NP\\NP)/(S/NP)
|
||||
... que => S[dep]/S
|
||||
... ''')
|
||||
|
||||
>>> parser = chart.CCGChartParser(lex, chart.DefaultRuleSet)
|
||||
>>> for parse in parser.parse(u"el ministro anunció pero el presidente desmintió la nueva ley".split()):
|
||||
... printCCGDerivation(parse) # doctest: +SKIP
|
||||
... # it fails on python2.7 because of the unicode problem explained in https://github.com/nltk/nltk/pull/1354
|
||||
... break
|
||||
el ministro anunció pero el presidente desmintió la nueva ley
|
||||
(NP/N) N ((S\NP)/NP) (((S/NP)\(S/NP))/(S/NP)) (NP/N) N ((S\NP)/NP) (NP/N) (N/N) N
|
||||
------------------>
|
||||
NP
|
||||
------------------>T
|
||||
(S/(S\NP))
|
||||
-------------------->
|
||||
NP
|
||||
-------------------->T
|
||||
(S/(S\NP))
|
||||
--------------------------------->B
|
||||
(S/NP)
|
||||
----------------------------------------------------------->
|
||||
((S/NP)\(S/NP))
|
||||
------------>
|
||||
N
|
||||
-------------------->
|
||||
NP
|
||||
--------------------<T
|
||||
(S\(S/NP))
|
||||
-------------------------------------------------------------------------------<B
|
||||
(S\(S/NP))
|
||||
--------------------------------------------------------------------------------------------<B
|
||||
(S/NP)
|
||||
-------------------------------------------------------------------------------------------------------------->
|
||||
S
|
||||
Reference in New Issue
Block a user