#### MEMORY-BASED SHALLOW PARSER ######################################################################
# Copyright (c) 2003-2010 University of Antwerp, Belgium and Tilburg University, The Netherlands
# License: GNU General Public License, see LICENSE.txt
######################################################################################################
# Add the upper directory (where the MBSP module is) to the search path.
import os, sys; sys.path.insert(0, os.path.join("..", ".."))
import MBSP
if not MBSP.config.autostart:
MBSP.start()
s = MBSP.parse("I eat pizza with a fork.")
s = MBSP.split(s) # Yields a list of traversable Sentence objects.
for sentence in s:
for chunk in sentence.chunks:
print repr(chunk)
print
print " Words:", chunk.words # A list of Word objects.
print " Relations:", chunk.related # A list of Chunk objects.
print " Parent PNP:", repr(chunk.pnp) # A PNPChunk object, or None.
print "Related PNP:", chunk.attachments # A list of PNPChunk objects.
print
# Remove the servers from memory when you're done:
# MBSP.stop()
#### MEMORY-BASED SHALLOW PARSER ######################################################################
# Copyright (c) 2003-2010 University of Antwerp, Belgium and Tilburg University, The Netherlands
# License: GNU General Public License, see LICENSE.txt
######################################################################################################
# Add the upper directory (where the MBSP module is) to the search path.
import os, sys; sys.path.insert(0, os.path.join("..", ".."))
import MBSP
if not MBSP.config.autostart:
MBSP.start()
s = MBSP.parse("I ate many slices of pizza with a fork.")
s = MBSP.split(s)
# A useful operation is to extract the heads in a sentence,
# for example to create a "normalized" sentence, or to construct a Timbl lookup instance.
# A head is the principal word in a chunk.
# We could retrieve the heads by iterating over Sentence.chunks,
# but this would skip the loose words in between chunks (e.g. "and" or ","),
# which can also be useful, particularly in the case of contructing a lookup instance.
# Sentence.constituents() returns an in-order list of mixed Chunk and Word objects
# that can be used for this purpose:
heads = []
for p in s[0].constituents(pnp=False):
if isinstance(p, MBSP.Word):
heads.append((
p.index,
p.lemma))
# Copyright (c) 2003-2010 University of Antwerp, Belgium and Tilburg University, The Netherlands
# License: GNU General Public License, see LICENSE.txt
######################################################################################################
# Add the upper directory (where the MBSP module is) to the search path.
import os, sys
sys.path.insert(0, os.path.join("..", ".."))
import MBSP
if not MBSP.config.autostart:
MBSP.start()
s = MBSP.parse("I eat pizza with a fork.")
s = MBSP.split(s) # Yields a list of traversable Sentence objects.
for sentence in s:
for chunk in sentence.chunks:
print repr(chunk)
print
print " Words:", chunk.words # A list of Word objects.
print " Relations:", chunk.related # A list of Chunk objects.
print " Parent PNP:", repr(chunk.pnp) # A PNPChunk object, or None.
print "Related PNP:", chunk.attachments # A list of PNPChunk objects.
print
# Remove the servers from memory when you're done:
# MBSP.stop()
