class DiscourseParser():
def __init__(self, verbose, seg, output, SGML, edus, feature_sets = 'FengHirst'):
''' This is Hilda's segmentation module '''
self.segmenter = None
self.verbose = verbose
self.seg = seg
self.output = output
self.SGML = SGML
self.edus = edus
self.dependencies = True
self.max_iters = 0
self.feature_sets = feature_sets
initStart = time.time()
try:
self.segmenter = Segmenter(_model_path = os.path.join(paths.SEG_MODEL_PATH), _model_file = "training.scaled.model", _scale_model_file = "bin_scale",
_name = "segmenter",
verbose = self.verbose, dependencies = self.dependencies)
except Exception, e:
print "*** Loading Segmentation module failed..."
if not self.segmenter is None:
self.segmenter.unload()
raise
self.treebuilder = None
try:
if self.feature_sets == 'FengHirst':
self.treebuilder = GreedyTreeBuilder(_model_path = paths.TREE_BUILD_MODEL_PATH,
_bin_model_file = ['struct/FengHirst/within_no_context.svmperf',
'struct/FengHirst/above_no_context.svmperf'],
_bin_scale_model_file = None,
_mc_model_file = ['label/FengHirst/within_label_nuclearity_no_context.multiclass',
'label/FengHirst/above_label_nuclearity_no_context.multiclass'],
_mc_scale_model_file = None,
_name = "FengHirst", verbose = self.verbose, use_contextual_features = False)
# else:
# self.treebuilder = TreeBuilder(_model_path = paths.INIT_TREE_BUILD_MODEL_PATH,
# _bin_model_file = 'struct/hilda/liblinear_bin_model.dat', _bin_scale_model_file = 'struct/hilda/bin_scale',
# _mc_model_file = 'label/hilda/libsvm_rbf_mc_model.dat', _mc_scale_model_file = 'label/hilda/mc_scale',
# _name = "hilda", verbose = self.verbose, use_contextual_features = False)
except Exception, e:
print "*** Loading Tree-building module failed..."
print traceback.print_exc()
if not self.treebuilder is None:
self.treebuilder.unload()
raise
def __init__(self, verbose, seg, output, SGML, edus, feature_sets = 'FengHirst'):
''' This is Hilda's segmentation module '''
self.segmenter = None
self.verbose = verbose
self.seg = seg
self.output = output
self.SGML = SGML
self.edus = edus
self.dependencies = True
self.max_iters = 0
self.feature_sets = feature_sets
initStart = time.time()
try:
self.segmenter = Segmenter(_model_path = os.path.join(paths.SEG_MODEL_PATH), _model_file = "training.scaled.model", _scale_model_file = "bin_scale",
_name = "segmenter",
verbose = self.verbose, dependencies = self.dependencies)
except Exception, e:
print "*** Loading Segmentation module failed..."
if not self.segmenter is None:
self.segmenter.unload()
raise
