def demo():
"""
A demonstration showing how each tree transform can be used.
"""
from en.parser.nltk_lite.draw.tree import draw_trees
from en.parser.nltk_lite.parse import bracket_parse
from en.parser.nltk_lite.parse import treetransforms
from copy import deepcopy
# original tree from WSJ bracketed text
sentence = "(TOP (S (S (VP (VBN Turned) (ADVP (RB loose)) (PP (IN in) (NP (NP (NNP Shane) (NNP Longman) (POS 's)) (NN trading) (NN room))))) (, ,) (NP (DT the) (NN yuppie) (NNS dealers)) (VP (AUX do) (NP (NP (RB little)) (ADJP (RB right)))) (. .)))"
tree = bracket_parse(sentence)
# collapse subtrees with only one child
collapsedTree = deepcopy(tree)
treetransforms.collapseUnary(collapsedTree)
# convert the tree to CNF
cnfTree = deepcopy(collapsedTree)
treetransforms.chomskyNormalForm(cnfTree)
# convert the tree to CNF with parent annotation (one level) and horizontal smoothing of order two
parentTree = deepcopy(collapsedTree)
treetransforms.chomskyNormalForm(parentTree, horzMarkov=2, vertMarkov=1)
# convert the tree back to its original form (used to make CYK results comparable)
original = deepcopy(parentTree)
treetransforms.unChomskyNormalForm(original)
# convert tree back to bracketed text
sentence2 = treetransforms.toTreebank(original)
print "Sentences the same? ", sentence == sentence2
draw_trees(tree, collapsedTree, cnfTree, parentTree, original)
def main():
import sys
from optparse import OptionParser, OptionGroup
usage = """%%prog [options] [grammar_file]""" % globals()
opts = OptionParser(usage=usage)
opts.add_option("-c",
"--components",
action="store_true",
dest="show_components",
default=0,
help="show hole semantics components")
opts.add_option("-r",
"--raw",
action="store_true",
dest="show_raw",
default=0,
help="show the raw hole semantics expression")
opts.add_option("-d",
"--drawtrees",
action="store_true",
dest="draw_trees",
default=0,
help="show formula trees in a GUI window")
opts.add_option("-v",
"--verbose",
action="count",
dest="verbosity",
default=0,
help="show more information during parse")
(options, args) = opts.parse_args()
if len(args) > 0:
filename = args[0]
else:
filename = 'hole.cfg'
print 'Reading grammar file', filename
grammar = GrammarFile.read_file(filename)
parser = grammar.earley_parser(trace=options.verbosity)
# Prompt the user for a sentence.
print 'Sentence: ',
line = sys.stdin.readline()[:-1]
# Parse the sentence.
tokens = list(tokenize.whitespace(line))
trees = parser.get_parse_list(tokens)
print 'Got %d different parses' % len(trees)
for tree in trees:
# Get the semantic feature from the top of the parse tree.
sem = tree[0].node['sem'].simplify()
# Skolemise away all quantifiers. All variables become unique.
sem = sem.skolemise()
# Reparse the semantic representation from its bracketed string format.
# I find this uniform structure easier to handle. It also makes the
# code mostly independent of the lambda calculus classes.
usr = bracket_parse(str(sem))
# Break the hole semantics representation down into its components
# i.e. holes, labels, formula fragments and constraints.
hole_sem = HoleSemantics(usr)
# Maybe print the raw semantic representation.
if options.show_raw:
print
print 'Raw expression'
print usr
# Maybe show the details of the semantic representation.
if options.show_components:
print
print 'Holes: ', hole_sem.holes
print 'Labels: ', hole_sem.labels
print 'Constraints: ', hole_sem.constraints
print 'Top hole: ', hole_sem.top_hole
print 'Top labels: ', hole_sem.top_most_labels
print 'Fragments:'
for (l, f) in hole_sem.fragments.items():
print '\t%s: %s' % (l, f)
# Find all the possible ways to plug the formulas together.
pluggings = hole_sem.pluggings()
# Build FOL formula trees using the pluggings.
trees = map(hole_sem.formula_tree, pluggings)
# Print out the formulas in a textual format.
n = 1
for tree in trees:
print
print '%d. %s' % (n, tree)
n += 1
# Maybe draw the formulas as trees.
if options.draw_trees:
draw_trees(*trees)
print
print 'Done.'
def main():
import sys
from optparse import OptionParser, OptionGroup
usage = """%%prog [options] [grammar_file]""" % globals()
opts = OptionParser(usage=usage)
opts.add_option("-c", "--components",
action="store_true", dest="show_components", default=0,
help="show hole semantics components")
opts.add_option("-r", "--raw",
action="store_true", dest="show_raw", default=0,
help="show the raw hole semantics expression")
opts.add_option("-d", "--drawtrees",
action="store_true", dest="draw_trees", default=0,
help="show formula trees in a GUI window")
opts.add_option("-v", "--verbose",
action="count", dest="verbosity", default=0,
help="show more information during parse")
(options, args) = opts.parse_args()
if len(args) > 0:
filename = args[0]
else:
filename = 'hole.cfg'
print 'Reading grammar file', filename
grammar = GrammarFile.read_file(filename)
parser = grammar.earley_parser(trace=options.verbosity)
# Prompt the user for a sentence.
print 'Sentence: ',
line = sys.stdin.readline()[:-1]
# Parse the sentence.
tokens = list(tokenize.whitespace(line))
trees = parser.get_parse_list(tokens)
print 'Got %d different parses' % len(trees)
for tree in trees:
# Get the semantic feature from the top of the parse tree.
sem = tree[0].node['sem'].simplify()
# Skolemise away all quantifiers. All variables become unique.
sem = sem.skolemise()
# Reparse the semantic representation from its bracketed string format.
# I find this uniform structure easier to handle. It also makes the
# code mostly independent of the lambda calculus classes.
usr = bracket_parse(str(sem))
# Break the hole semantics representation down into its components
# i.e. holes, labels, formula fragments and constraints.
hole_sem = HoleSemantics(usr)
# Maybe print the raw semantic representation.
if options.show_raw:
print
print 'Raw expression'
print usr
# Maybe show the details of the semantic representation.
if options.show_components:
print
print 'Holes: ', hole_sem.holes
print 'Labels: ', hole_sem.labels
print 'Constraints: ', hole_sem.constraints
print 'Top hole: ', hole_sem.top_hole
print 'Top labels: ', hole_sem.top_most_labels
print 'Fragments:'
for (l,f) in hole_sem.fragments.items():
print '\t%s: %s' % (l, f)
# Find all the possible ways to plug the formulas together.
pluggings = hole_sem.pluggings()
# Build FOL formula trees using the pluggings.
trees = map(hole_sem.formula_tree, pluggings)
# Print out the formulas in a textual format.
n = 1
for tree in trees:
print
print '%d. %s' % (n, tree)
n += 1
# Maybe draw the formulas as trees.
if options.draw_trees:
draw_trees(*trees)
print
print 'Done.'
