import sys
import os
import re
import collections
sys.path.append(
os.path.join(os.path.dirname(__file__), '..', '..', 'resource-gcg',
'scripts'))
import tree
import gcgtree
for line in sys.stdin:
print(gcgtree.GCGTree(line))
import sys
import os
import re
import collections
sys.path.append(
os.path.join(os.path.dirname(__file__), '..', '..', 'resource-gcg',
'scripts'))
import tree
import gcgtree
for line in sys.stdin:
print(gcgtree.GCGTree(
line.strip())) #strip to prevent adding additional blank lines
t.c += xy
else:
t.c += '-x%' + morph.getLemma(t.c,t.ch[0].c) + '|%Bot'
for st in t.ch:
ctr = annotY( st, Ymap, ctr )
return ctr
################################################################################
################################################################################
## read in corpus and convert to traversal trees...
lt = [ ]
llpttrav = [ ]
for line in sys.stdin:
Marked = { }
lt.append( gcgtree.GCGTree(line) )
# print( semcuegraph.StoreStateCueGraph(lt[-1]) )
numberTerminals( lt[-1] )
lptFactored = factorConj( lt[-1] )
llpttrav.append( [ (p,t,makeTraversal(semcuegraph.SimpleCueGraph(semcuegraph.SemCueGraph(t)),Marked)) for p,t in lptFactored ] )
# for p,t in lptFactored:
# print( '==FULL==>', str( semcuegraph.SemCueGraph(t) ) )
# print( '--SIMPLE->', str( semcuegraph.SimpleCueGraph(semcuegraph.SemCueGraph(t)) ) )
## set size params...
K,L = 0,0
for lpttrav in llpttrav:
for p,t,trav in lpttrav:
K,l = setKL( trav, KINTS )
L = max(L,l)
sys.stderr.write( str(K) + ' predicate constants, ' + str(L) + ' dependency labels.\n' )
## Define discourse graph...
G = semcuegraph.SemCueGraph( )
sentctr = 0
## For each sentence...
for line in sys.stdin:
if '!ARTICLE' in line: break
if sentctr == 0:
discctr += 1
sys.stderr.write( 'Discourse ' + str(discctr) + ': ' + line )
## Initialize new tree with or without tree-lengthening...
if RELABEL:
t = gcgtree.GCGTree( line )
else:
t = tree.Tree( )
t.read( line )
## Add tree to discourse graph...
G.add( t, ('0' if sentctr<10 else '') + str(sentctr) )
sentctr += 1
else: finished = True
## If discourse contained any sentences, finalize and print graph...
if sentctr>0:
G.finalize()
print( str(G) )