nltk.parse.malt.MaltParser

class documentation

class MaltParser(ParserI): (source)

Constructor: MaltParser(parser_dirname, model_filename, tagger, additional_java_args)

A class for dependency parsing with MaltParser. The input is the paths to: - a maltparser directory - (optionally) the path to a pre-trained MaltParser .mco model file - (optionally) the tagger to use for POS tagging before parsing - (optionally) additional Java arguments

Example:

>>> from nltk.parse import malt
>>> # With MALT_PARSER and MALT_MODEL environment set.
>>> mp = malt.MaltParser('maltparser-1.7.2', 'engmalt.linear-1.7.mco') # doctest: +SKIP
>>> mp.parse_one('I shot an elephant in my pajamas .'.split()).tree() # doctest: +SKIP
(shot I (elephant an) (in (pajamas my)) .)
>>> # Without MALT_PARSER and MALT_MODEL environment.
>>> mp = malt.MaltParser('/home/user/maltparser-1.7.2/', '/home/user/engmalt.linear-1.7.mco') # doctest: +SKIP
>>> mp.parse_one('I shot an elephant in my pajamas .'.split()).tree() # doctest: +SKIP
(shot I (elephant an) (in (pajamas my)) .)

Method	`__init__`	An interface for parsing with the Malt Parser.
Method	`generate_malt_command`	This function generates the maltparser command use at the terminal.
Method	`parse_sents`	Use MaltParser to parse multiple sentences. Takes a list of sentences, where each sentence is a list of words. Each sentence will be automatically tagged with this MaltParser instance's tagger.
Method	`parse_tagged_sents`	Use MaltParser to parse multiple POS tagged sentences. Takes multiple sentences where each sentence is a list of (word, tag) tuples. The sentences must have already been tokenized and tagged.
Method	`train`	Train MaltParser from a list of `DependencyGraph` objects
Method	`train_from_file`	Train MaltParser from a file :param conll_file: str for the filename of the training input data :type conll_file: str
Instance Variable	`additional_java_args`	Undocumented
Instance Variable	`malt_jars`	Undocumented
Instance Variable	`model`	Undocumented
Instance Variable	`tagger`	Undocumented
Instance Variable	`working_dir`	Undocumented
Static Method	`_execute`	Undocumented
Instance Variable	`_trained`	Undocumented

Inherited from ParserI:

Method	`grammar`	No summary
Method	`parse`	When possible this list is sorted from most likely to least likely.
Method	`parse_all`	No summary
Method	`parse_one`	No summary

def __init__(self, parser_dirname, model_filename=None, tagger=None, additional_java_args=None): (source) ¶

An interface for parsing with the Malt Parser.

contains the maltparser-1.x.jar :type parser_dirname: str :param model_filename: The name of the pre-trained model with .mco file extension. If provided, training will not be required. (see http://www.maltparser.org/mco/mco.html and see http://www.patful.com/chalk/node/185) :type model_filename: str :param tagger: The tagger used to POS tag the raw string before formatting to CONLL format. It should behave like nltk.pos_tag :type tagger: function :param additional_java_args: This is the additional Java arguments that one can use when calling Maltparser, usually this is the heapsize limits, e.g. additional_java_args=['-Xmx1024m'] (see http://goo.gl/mpDBvQ) :type additional_java_args: list

Parameters
parser_dirname	The path to the maltparser directory that
model_filename	Undocumented
tagger	Undocumented
additional_java_args	Undocumented

def generate_malt_command(self, inputfilename, outputfilename=None, mode=None): (source) ¶

This function generates the maltparser command use at the terminal.

Parameters
inputfilename:str	path to the input file
outputfilename:str	path to the output file
mode	Undocumented

def parse_sents(self, sentences, verbose=False, top_relation_label='null'): (source) ¶

overrides nltk.parse.api.ParserI.parse_sents

Use MaltParser to parse multiple sentences. Takes a list of sentences, where each sentence is a list of words. Each sentence will be automatically tagged with this MaltParser instance's tagger.

Parameters
sentences	Input sentences to parse
verbose	Undocumented
top_relation_label	Undocumented
sentence:list(list(str))	Undocumented
Returns
iter(DependencyGraph)

def parse_tagged_sents(self, sentences, verbose=False, top_relation_label='null'): (source) ¶

Use MaltParser to parse multiple POS tagged sentences. Takes multiple sentences where each sentence is a list of (word, tag) tuples. The sentences must have already been tokenized and tagged.

representation of each sentence

Parameters
sentences	Input sentences to parse
verbose	Undocumented
top_relation_label	Undocumented
sentence:list(list(tuple(str, str)))	Undocumented
Returns
iter(iter(`DependencyGraph`)) the dependency graph