with open("sentences2.csv") as f:
reader = csv.reader(f)
next(reader) # skip headers
sentence_number = 0
for row in reader:
sentence_number += 1
print "Sentence #%d" % sentence_number
# unpack row and convert to the rigth types
location, region, nearfar, precise, utterance, parse = row
location = int(location) / 100.0
# precise = (precise == 'T')
# sample landmark, relation and degree
for j in range(iters):
lmk_name, lmk_loc = sample_landmark(location)
relation, degree = sample_reldeg(location, lmk_loc)
# parse sentence
# parse = parse_sentence(phrase)['parsetree']
rel_words, lmk_words, rel_phrases, lmk_phrases = modify_parse(parse)
if verbose:
print "-" * 70
print "Utterance: %r" % utterance
print "Location: %s" % location
print "Landmark: %s (%s)" % (lmk_loc, lmk_name)
print "Relation: %s" % relation
print "Degree: %s" % degree
print "Parse tree:\n%s" % parse
# print 'Modified parse tree:\n%s' % modparse
# print 'Parse tree as list:\n%s' % pf(lparse)
# print 'Modified parse tree as list:\n%s' % pf(lmodparse)
sentence_number = 0
for row in reader:
sentence_number += 1
print 'Sentence #%d' % sentence_number
# unpack row and convert to the rigth types
location, region, nearfar, precise, utterance, parse = row
location = int(location) / 100.0
# precise = (precise == 'T')
# parse sentence
# parse = parse_sentence(phrase)['parsetree']
rel_words, lmk_words, rel_phrases, lmk_phrases = modify_parse(
parse)
# sample landmark, relation and degree
for j in range(iters):
lmk_name, lmk_loc = sample_landmark(location)
relation, degree = sample_reldeg(lmk_loc, location)
if verbose:
print '-' * 70
print 'Utterance: %r' % utterance
print 'Location: %s' % location
print 'Landmark: %s (%s)' % (lmk_loc, lmk_name)
print 'Relation: %s' % relation
print 'Degree: %s' % degree
print 'Parse tree:\n%s' % parse
#print 'Modified parse tree:\n%s' % modparse
#print 'Parse tree as list:\n%s' % pf(lparse)
#print 'Modified parse tree as list:\n%s' % pf(lmodparse)
#print 'Relation chunk:\n%s' % pf(rel_chunk)
#print 'Landmark chunk:\n%s' % pf(lmk_chunk)
print 'Relation structure: %s' % rel_phrases[0][1]
next(reader) # skip headers
sentence_number = 0
for row in reader:
sentence_number += 1
print 'Sentence #%d' % sentence_number
# unpack row and convert to the rigth types
location, region, nearfar, precise, utterance, parse = row
location = int(location) / 100.0
# precise = (precise == 'T')
# parse sentence
# parse = parse_sentence(phrase)['parsetree']
rel_words, lmk_words, rel_phrases, lmk_phrases = modify_parse(parse)
# sample landmark, relation and degree
for j in range(iters):
lmk_name, lmk_loc = sample_landmark(location)
relation, degree = sample_reldeg(lmk_loc, location)
if verbose:
print '-' * 70
print 'Utterance: %r' % utterance
print 'Location: %s' % location
print 'Landmark: %s (%s)' % (lmk_loc, lmk_name)
print 'Relation: %s' % relation
print 'Degree: %s' % degree
print 'Parse tree:\n%s' % parse
#print 'Modified parse tree:\n%s' % modparse
#print 'Parse tree as list:\n%s' % pf(lparse)
#print 'Modified parse tree as list:\n%s' % pf(lmodparse)
#print 'Relation chunk:\n%s' % pf(rel_chunk)
#print 'Landmark chunk:\n%s' % pf(lmk_chunk)
print 'Relation structure: %s' % rel_phrases[0][1]