nltk.inference.discourse module

Module for incrementally developing simple discourses, and checking for semantic ambiguity, consistency and informativeness.

Many of the ideas are based on the CURT family of programs of Blackburn and Bos (see http://homepages.inf.ed.ac.uk/jbos/comsem/book1.html).

Consistency checking is carried out by using the mace module to call the Mace4 model builder. Informativeness checking is carried out with a call to Prover.prove() from the inference module.

DiscourseTester is a constructor for discourses. The basic data structure is a list of sentences, stored as self._sentences. Each sentence in the list is assigned a “sentence ID” (sid) of the form si. For example:

s0: A boxer walks
s1: Every boxer chases a girl

Each sentence can be ambiguous between a number of readings, each of which receives a “reading ID” (rid) of the form si -rj. For example:

s0 readings:

s0-r1: some x.(boxer(x) & walk(x))
s0-r0: some x.(boxerdog(x) & walk(x))

A “thread” is a list of readings, represented as a list of rids. Each thread receives a “thread ID” (tid) of the form di. For example:

d0: ['s0-r0', 's1-r0']

The set of all threads for a discourse is the Cartesian product of all the readings of the sequences of sentences. (This is not intended to scale beyond very short discourses!) The method readings(filter=True) will only show those threads which are consistent (taking into account any background assumptions).

class nltk.inference.discourse.CfgReadingCommand

Bases: ReadingCommand

__init__(gramfile=None)

Parameters

gramfile (str) – name of file where grammar can be loaded

combine_readings(readings)

See

ReadingCommand.combine_readings()

parse_to_readings(sentence)

See

ReadingCommand.parse_to_readings()

to_fol(expression)

See

ReadingCommand.to_fol()

class nltk.inference.discourse.DiscourseTester

Bases: object

Check properties of an ongoing discourse.

__init__(input, reading_command=None, background=None)

Initialize a DiscourseTester.

Parameters

• input (list of str) – the discourse sentences

• background (list(Expression)) – Formulas which express background assumptions

add_background(background, verbose=False)

Add a list of background assumptions for reasoning about the discourse.

When called, this method also updates the discourse model’s set of readings and threads. :param background: Formulas which contain background information :type background: list(Expression)

add_sentence(sentence, informchk=False, consistchk=False)

Add a sentence to the current discourse.

Updates self._input and self._sentences. :param sentence: An input sentence :type sentence: str :param informchk: if True, check that the result of adding the sentence is thread-informative. Updates self._readings. :param consistchk: if True, check that the result of adding the sentence is thread-consistent. Updates self._readings.

background()

Show the current background assumptions.

expand_threads(thread_id, threads=None)

Given a thread ID, find the list of logic.Expression objects corresponding to the reading IDs in that thread.

Parameters

• thread_id (str) – thread ID

• threads (dict) – a mapping from thread IDs to lists of reading IDs

Returns

A list of pairs (rid, reading) where reading is the logic.Expression associated with a reading ID

Return type

list of tuple

grammar()

Print out the grammar in use for parsing input sentences

models(thread_id=None, show=True, verbose=False)

Call Mace4 to build a model for each current discourse thread.

Parameters

• thread_id (str) – thread ID

• show – If True, display the model that has been found.

static multiply(discourse, readings)

Multiply every thread in discourse by every reading in readings.

Given discourse = [[‘A’], [‘B’]], readings = [‘a’, ‘b’, ‘c’] , returns [[‘A’, ‘a’], [‘A’, ‘b’], [‘A’, ‘c’], [‘B’, ‘a’], [‘B’, ‘b’], [‘B’, ‘c’]]

Parameters

• discourse (list of lists) – the current list of readings

• readings (list(Expression)) – an additional list of readings

Return type

A list of lists

readings(sentence=None, threaded=False, verbose=True, filter=False, show_thread_readings=False)

Construct and show the readings of the discourse (or of a single sentence).

Parameters

• sentence (str) – test just this sentence

• threaded – if True, print out each thread ID and the corresponding thread.

• filter – if True, only print out consistent thread IDs and threads.

retract_sentence(sentence, verbose=True)

Remove a sentence from the current discourse.

Updates self._input, self._sentences and self._readings. :param sentence: An input sentence :type sentence: str :param verbose: If True, report on the updated list of sentences.

sentences()

Display the list of sentences in the current discourse.

class nltk.inference.discourse.DrtGlueReadingCommand

Bases: ReadingCommand

__init__(semtype_file=None, remove_duplicates=False, depparser=None)

Parameters

• semtype_file – name of file where grammar can be loaded

• remove_duplicates – should duplicates be removed?

• depparser – the dependency parser

combine_readings(readings)

See

ReadingCommand.combine_readings()

parse_to_readings(sentence)

See

ReadingCommand.parse_to_readings()

process_thread(sentence_readings)

See

ReadingCommand.process_thread()

to_fol(expression)

See

ReadingCommand.to_fol()

class nltk.inference.discourse.ReadingCommand

Bases: object

abstract combine_readings(readings)

Parameters

readings (list(Expression)) – readings to combine

Returns

one combined reading

Return type

Expression

abstract parse_to_readings(sentence)

Parameters

sentence (str) – the sentence to read

process_thread(sentence_readings)

This method should be used to handle dependencies between readings such as resolving anaphora.

Parameters

sentence_readings (list(Expression)) – readings to process

Returns

the list of readings after processing

Return type

list(Expression)

abstract to_fol(expression)

Convert this expression into a First-Order Logic expression.

Parameters

expression (Expression) – an expression

Returns

a FOL version of the input expression

Return type

Expression

nltk.inference.discourse.demo()

nltk.inference.discourse.discourse_demo(reading_command=None)

Illustrate the various methods of DiscourseTester

nltk.inference.discourse.drt_discourse_demo(reading_command=None)

Illustrate the various methods of DiscourseTester

nltk.inference.discourse.load_fol(s)

Temporarily duplicated from nltk.sem.util. Convert a file of first order formulas into a list of Expression objects.

Parameters

s (str) – the contents of the file

Returns

a list of parsed formulas.

Return type

list(Expression)

nltk.inference.discourse.spacer(num=30)