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# -*- coding: utf-8 -*- # Natural Language Toolkit: Context Free Grammars # # Copyright (C) 2001-2012 NLTK Project # Author: Steven Bird <sb@csse.unimelb.edu.au> # Edward Loper <edloper@seas.upenn.edu> # Jason Narad <jason.narad@gmail.com> # Peter Ljunglöf <peter.ljunglof@heatherleaf.se> # URL: <http://www.nltk.org/> # For license information, see LICENSE.TXT #
Basic data classes for representing context free grammars. A "grammar" specifies which trees can represent the structure of a given text. Each of these trees is called a "parse tree" for the text (or simply a "parse"). In a "context free" grammar, the set of parse trees for any piece of a text can depend only on that piece, and not on the rest of the text (i.e., the piece's context). Context free grammars are often used to find possible syntactic structures for sentences. In this context, the leaves of a parse tree are word tokens; and the node values are phrasal categories, such as ``NP`` and ``VP``.
The ``ContextFreeGrammar`` class is used to encode context free grammars. Each ``ContextFreeGrammar`` consists of a start symbol and a set of productions. The "start symbol" specifies the root node value for parse trees. For example, the start symbol for syntactic parsing is usually ``S``. Start symbols are encoded using the ``Nonterminal`` class, which is discussed below.
A Grammar's "productions" specify what parent-child relationships a parse tree can contain. Each production specifies that a particular node can be the parent of a particular set of children. For example, the production ``<S> -> <NP> <VP>`` specifies that an ``S`` node can be the parent of an ``NP`` node and a ``VP`` node.
Grammar productions are implemented by the ``Production`` class. Each ``Production`` consists of a left hand side and a right hand side. The "left hand side" is a ``Nonterminal`` that specifies the node type for a potential parent; and the "right hand side" is a list that specifies allowable children for that parent. This lists consists of ``Nonterminals`` and text types: each ``Nonterminal`` indicates that the corresponding child may be a ``TreeToken`` with the specified node type; and each text type indicates that the corresponding child may be a ``Token`` with the with that type.
The ``Nonterminal`` class is used to distinguish node values from leaf values. This prevents the grammar from accidentally using a leaf value (such as the English word "A") as the node of a subtree. Within a ``ContextFreeGrammar``, all node values are wrapped in the ``Nonterminal`` class. Note, however, that the trees that are specified by the grammar do *not* include these ``Nonterminal`` wrappers.
Grammars can also be given a more procedural interpretation. According to this interpretation, a Grammar specifies any tree structure *tree* that can be produced by the following procedure:
| Set tree to the start symbol | Repeat until tree contains no more nonterminal leaves: | Choose a production prod with whose left hand side | lhs is a nonterminal leaf of tree. | Replace the nonterminal leaf with a subtree, whose node | value is the value wrapped by the nonterminal lhs, and | whose children are the right hand side of prod.
The operation of replacing the left hand side (*lhs*) of a production with the right hand side (*rhs*) in a tree (*tree*) is known as "expanding" *lhs* to *rhs* in *tree*. """
################################################################# # Nonterminal #################################################################
""" A non-terminal symbol for a context free grammar. ``Nonterminal`` is a wrapper class for node values; it is used by ``Production`` objects to distinguish node values from leaf values. The node value that is wrapped by a ``Nonterminal`` is known as its "symbol". Symbols are typically strings representing phrasal categories (such as ``"NP"`` or ``"VP"``). However, more complex symbol types are sometimes used (e.g., for lexicalized grammars). Since symbols are node values, they must be immutable and hashable. Two ``Nonterminals`` are considered equal if their symbols are equal.
:see: ``ContextFreeGrammar``, ``Production`` :type _symbol: any :ivar _symbol: The node value corresponding to this ``Nonterminal``. This value must be immutable and hashable. """ """ Construct a new non-terminal from the given symbol.
:type symbol: any :param symbol: The node value corresponding to this ``Nonterminal``. This value must be immutable and hashable. """
""" Return the node value corresponding to this ``Nonterminal``.
:rtype: (any) """
""" Return True if this non-terminal is equal to ``other``. In particular, return True if ``other`` is a ``Nonterminal`` and this non-terminal's symbol is equal to ``other`` 's symbol.
:rtype: bool """ and isinstance(other, self.__class__))
return not (self == other)
if not isinstance(other, self.__class__): # XXX: self.__class__ vs Nonterminal? return False return self._symbol < other._symbol
""" Return a string representation for this ``Nonterminal``.
:rtype: str """ else: return '%r' % (self._symbol,)
""" Return a string representation for this ``Nonterminal``.
:rtype: str """ if isinstance(self._symbol, string_types): return '%s' % (self._symbol,) else: return '%r' % (self._symbol,)
""" Return a new nonterminal whose symbol is ``A/B``, where ``A`` is the symbol for this nonterminal, and ``B`` is the symbol for rhs.
:param rhs: The nonterminal used to form the right hand side of the new nonterminal. :type rhs: Nonterminal :rtype: Nonterminal """ return Nonterminal('%s/%s' % (self._symbol, rhs._symbol))
""" Given a string containing a list of symbol names, return a list of ``Nonterminals`` constructed from those symbols.
:param symbols: The symbol name string. This string can be delimited by either spaces or commas. :type symbols: str :return: A list of ``Nonterminals`` constructed from the symbol names given in ``symbols``. The ``Nonterminals`` are sorted in the same order as the symbols names. :rtype: list(Nonterminal) """ else: symbol_list = symbols.split()
"""A feature structure that's also a nonterminal. It acts as its own symbol, and automatically freezes itself when hashed."""
""" :return: True if the item is a ``Nonterminal``. :rtype: bool """
################################################################# # Terminals #################################################################
""" Return True if the item is a terminal, which currently is if it is hashable and not a ``Nonterminal``.
:rtype: bool """
################################################################# # Productions #################################################################
""" A grammar production. Each production maps a single symbol on the "left-hand side" to a sequence of symbols on the "right-hand side". (In the case of context-free productions, the left-hand side must be a ``Nonterminal``, and the right-hand side is a sequence of terminals and ``Nonterminals``.) "terminals" can be any immutable hashable object that is not a ``Nonterminal``. Typically, terminals are strings representing words, such as ``"dog"`` or ``"under"``.
:see: ``ContextFreeGrammar`` :see: ``DependencyGrammar`` :see: ``Nonterminal`` :type _lhs: Nonterminal :ivar _lhs: The left-hand side of the production. :type _rhs: tuple(Nonterminal, terminal) :ivar _rhs: The right-hand side of the production. """
""" Construct a new ``Production``.
:param lhs: The left-hand side of the new ``Production``. :type lhs: Nonterminal :param rhs: The right-hand side of the new ``Production``. :type rhs: sequence(Nonterminal and terminal) """ raise TypeError('production right hand side should be a list, ' 'not a string')
""" Return the left-hand side of this ``Production``.
:rtype: Nonterminal """
""" Return the right-hand side of this ``Production``.
:rtype: sequence(Nonterminal and terminal) """
""" Return the length of the right-hand side.
:rtype: int """
""" Return True if the right-hand side only contains ``Nonterminals``
:rtype: bool """
""" Return True if the right-hand contain at least one terminal token.
:rtype: bool """
""" Return a verbose string representation of the ``Production``.
:rtype: str """
""" Return a concise string representation of the ``Production``.
:rtype: str """
""" Return True if this ``Production`` is equal to ``other``.
:rtype: bool """ self._lhs == other._lhs and self._rhs == other._rhs)
return not (self == other)
if not isinstance(other, self.__class__): return False return (self._lhs, self._rhs) < (other._lhs, other._rhs)
""" Return a hash value for the ``Production``.
:rtype: int """
""" A dependency grammar production. Each production maps a single head word to an unordered list of one or more modifier words. """ """ Return a verbose string representation of the ``DependencyProduction``.
:rtype: str """
""" A probabilistic context free grammar production. A PCFG ``WeightedProduction`` is essentially just a ``Production`` that has an associated probability, which represents how likely it is that this production will be used. In particular, the probability of a ``WeightedProduction`` records the likelihood that its right-hand side is the correct instantiation for any given occurrence of its left-hand side.
:see: ``Production`` """ """ Construct a new ``WeightedProduction``.
:param lhs: The left-hand side of the new ``WeightedProduction``. :type lhs: Nonterminal :param rhs: The right-hand side of the new ``WeightedProduction``. :type rhs: sequence(Nonterminal and terminal) :param prob: Probability parameters of the new ``WeightedProduction``. """
return (isinstance(other, self.__class__) and self._lhs == other._lhs and self._rhs == other._rhs and self.prob() == other.prob())
return not (self == other)
################################################################# # Grammars #################################################################
""" A context-free grammar. A grammar consists of a start state and a set of productions. The set of terminals and nonterminals is implicitly specified by the productions.
If you need efficient key-based access to productions, you can use a subclass to implement it. """ """ Create a new context-free grammar, from the given start state and set of ``Production``s.
:param start: The start symbol :type start: Nonterminal :param productions: The list of productions that defines the grammar :type productions: list(Production) :param calculate_leftcorners: False if we don't want to calculate the leftcorner relation. In that case, some optimized chart parsers won't work. :type calculate_leftcorners: bool """
# Left hand side. # First item in right hand side. else: # The right hand side is empty. self._empty_index[prod.lhs()] = prod # Lexical tokens in the right hand side.
# Calculate leftcorner relations, for use in optimized parsing. else:
# If the grammar is big, the leftcorner-word dictionary will be too large. # In that case it is better to calculate the relation on demand. self._leftcorner_words = None return
""" Return the start symbol of the grammar
:rtype: Nonterminal """
# tricky to balance readability and efficiency here! # can't use set operations as they don't preserve ordering """ Return the grammar productions, filtered by the left-hand side or the first item in the right-hand side.
:param lhs: Only return productions with the given left-hand side. :param rhs: Only return productions with the given first item in the right-hand side. :param empty: Only return productions with an empty right-hand side. :return: A list of productions matching the given constraints. :rtype: list(Production) """ raise ValueError("You cannot select empty and non-empty " "productions at the same time.")
# no constraints so return everything else:
# only lhs specified so look up its index elif lhs in self._empty_index: return [self._empty_index[lhs]] else: return []
# only rhs specified so look up its index
# intersect else: return [prod for prod in self._lhs_index.get(lhs, []) if prod in self._rhs_index.get(rhs, [])]
""" Return the set of all nonterminals that the given nonterminal can start with, including itself.
This is the reflexive, transitive closure of the immediate leftcorner relation: (A > B) iff (A -> B beta)
:param cat: the parent of the leftcorners :type cat: Nonterminal :return: the set of all leftcorners :rtype: set(Nonterminal) """ return self._leftcorners.get(cat, set([cat]))
""" True if left is a leftcorner of cat, where left can be a terminal or a nonterminal.
:param cat: the parent of the leftcorner :type cat: Nonterminal :param left: the suggested leftcorner :type left: Terminal or Nonterminal :rtype: bool """ return left in self.leftcorners(cat) else: return any([left in _immediate_leftcorner_words.get(parent, set()) for parent in self.leftcorners(cat)])
""" Return the set of all nonterminals for which the given category is a left corner. This is the inverse of the leftcorner relation.
:param cat: the suggested leftcorner :type cat: Nonterminal :return: the set of all parents to the leftcorner :rtype: set(Nonterminal) """ return self._leftcorner_parents.get(cat, set([cat]))
""" Check whether the grammar rules cover the given list of tokens. If not, then raise an exception.
:type tokens: list(str) """ if not self._lexical_index.get(tok)] missing = ', '.join('%r' % (w,) for w in missing) raise ValueError("Grammar does not cover some of the " "input words: %r." % missing)
""" Pre-calculate of which form(s) the grammar is. """ if len(p) != 1]) if len(p) == 1])
""" Return True if all productions are lexicalised. """ return self._is_lexical
""" Return True if all lexical rules are "preterminals", that is, unary rules which can be separated in a preprocessing step.
This means that all productions are of the forms A -> B1 ... Bn (n>=0), or A -> "s".
Note: is_lexical() and is_nonlexical() are not opposites. There are grammars which are neither, and grammars which are both. """ return self._is_nonlexical
""" Return the right-hand side length of the shortest grammar production. """ return self._min_len
""" Return the right-hand side length of the longest grammar production. """ return self._max_len
""" Return True if there are no empty productions. """
""" Return True if all productions are at most binary. Note that there can still be empty and unary productions. """ return self._max_len <= 2
""" Return True if all productions are of the forms A -> B C, A -> B, or A -> "s". """ return self.is_nonempty() and self.is_nonlexical() and self.is_binarised()
""" Return True if the grammar is of Chomsky Normal Form, i.e. all productions are of the form A -> B C, or A -> "s". """ return (self.is_flexible_chomsky_normal_form() and self._all_unary_are_lexical)
""" A feature-based grammar. This is equivalent to a ``ContextFreeGrammar`` whose nonterminals are all ``FeatStructNonterminal``.
A grammar consists of a start state and a set of productions. The set of terminals and nonterminals is implicitly specified by the productions. """ """ Create a new feature-based grammar, from the given start state and set of ``Productions``.
:param start: The start symbol :type start: FeatStructNonterminal :param productions: The list of productions that defines the grammar :type productions: list(Production) """
# The difference with CFG is that the productions are # indexed on the TYPE feature of the nonterminals. # This is calculated by the method _get_type_if_possible().
# Left hand side. # First item in right hand side. else: # The right hand side is empty. # Lexical tokens in the right hand side.
""" Return the grammar productions, filtered by the left-hand side or the first item in the right-hand side.
:param lhs: Only return productions with the given left-hand side. :param rhs: Only return productions with the given first item in the right-hand side. :param empty: Only return productions with an empty right-hand side. :rtype: list(Production) """ raise ValueError("You cannot select empty and non-empty " "productions at the same time.")
# no constraints so return everything else:
# only lhs specified so look up its index return self._empty_index.get(self._get_type_if_possible(lhs), []) else:
# only rhs specified so look up its index
# intersect else: return [prod for prod in self._lhs_index.get(self._get_type_if_possible(lhs), []) if prod in self._rhs_index.get(self._get_type_if_possible(rhs), [])]
""" Return the set of all words that the given category can start with. Also called the "first set" in compiler construction. """ raise NotImplementedError("Not implemented yet")
""" Return the set of all categories for which the given category is a left corner. """ raise NotImplementedError("Not implemented yet")
""" Helper function which returns the ``TYPE`` feature of the ``item``, if it exists, otherwise it returns the ``item`` itself """ else:
""" A helper class for ``FeatureGrammars``, designed to be different from ordinary strings. This is to stop the ``FeatStruct`` ``FOO[]`` from being compare equal to the terminal "FOO". """
return '<%s>' % self._value
return False
return not (self == other)
if other.__class__ != FeatureValueType: return True return self._value < other._value
""" A dependency grammar. A DependencyGrammar consists of a set of productions. Each production specifies a head/modifier relationship between a pair of words. """ """ Create a new dependency grammar, from the set of ``Productions``.
:param productions: The list of productions that defines the grammar :type productions: list(Production) """
""" :param head: A head word. :type head: str :param mod: A mod word, to test as a modifier of 'head'. :type mod: str
:return: true if this ``DependencyGrammar`` contains a ``DependencyProduction`` mapping 'head' to 'mod'. :rtype: bool """
""" Return True if this ``DependencyGrammar`` contains a ``DependencyProduction`` mapping 'head' to 'mod'.
:param head: A head word. :type head: str :param mod: A mod word, to test as a modifier of 'head'. :type mod: str :rtype: bool """ for production in self._productions: for possibleMod in production._rhs: if(production._lhs == head and possibleMod == mod): return True return False
# # should be rewritten, the set comp won't work in all comparisons # def contains_exactly(self, head, modlist): # for production in self._productions: # if(len(production._rhs) == len(modlist)): # if(production._lhs == head): # set1 = Set(production._rhs) # set2 = Set(modlist) # if(set1 == set2): # return True # return False
""" Return a verbose string representation of the ``DependencyGrammar``
:rtype: str """
""" Return a concise string representation of the ``DependencyGrammar`` """ return 'Dependency grammar with %d productions' % len(self._productions)
"""
"""
self._productions = productions self._events = events self._tags = tags
""" Return True if this ``DependencyGrammar`` contains a ``DependencyProduction`` mapping 'head' to 'mod'.
:param head: A head word. :type head: str :param mod: A mod word, to test as a modifier of 'head'. :type mod: str :rtype: bool """ for production in self._productions: for possibleMod in production._rhs: if(production._lhs == head and possibleMod == mod): return True return False
""" Return a verbose string representation of the ``StatisticalDependencyGrammar``
:rtype: str """ str = 'Statistical dependency grammar with %d productions' % len(self._productions) for production in self._productions: str += '\n %s' % production str += '\nEvents:' for event in self._events: str += '\n %d:%s' % (self._events[event], event) str += '\nTags:' for tag_word in self._tags: str += '\n %s:\t(%s)' % (tag_word, self._tags[tag_word]) return str
""" Return a concise string representation of the ``StatisticalDependencyGrammar`` """ return 'Statistical Dependency grammar with %d productions' % len(self._productions)
""" A probabilistic context-free grammar. A Weighted Grammar consists of a start state and a set of weighted productions. The set of terminals and nonterminals is implicitly specified by the productions.
PCFG productions should be ``WeightedProductions``. ``WeightedGrammars`` impose the constraint that the set of productions with any given left-hand-side must have probabilities that sum to 1.
If you need efficient key-based access to productions, you can use a subclass to implement it.
:type EPSILON: float :cvar EPSILON: The acceptable margin of error for checking that productions with a given left-hand side have probabilities that sum to 1. """
""" Create a new context-free grammar, from the given start state and set of ``WeightedProductions``.
:param start: The start symbol :type start: Nonterminal :param productions: The list of productions that defines the grammar :type productions: list(Production) :raise ValueError: if the set of productions with any left-hand-side do not have probabilities that sum to a value within EPSILON of 1. :param calculate_leftcorners: False if we don't want to calculate the leftcorner relation. In that case, some optimized chart parsers won't work. :type calculate_leftcorners: bool """
# Make sure that the probabilities sum to one. production.prob()) (1+WeightedGrammar.EPSILON)): raise ValueError("Productions for %r do not sum to 1" % lhs)
################################################################# # Inducing Grammars #################################################################
# Contributed by Nathan Bodenstab <bodenstab@cslu.ogi.edu>
""" Induce a PCFG grammar from a list of productions.
The probability of a production A -> B C in a PCFG is:
| count(A -> B C) | P(B, C | A) = --------------- where \* is any right hand side | count(A -> \*)
:param start: The start symbol :type start: Nonterminal :param productions: The list of productions that defines the grammar :type productions: list(Production) """
# Production count: the number of times a given production occurs
# LHS-count: counts the number of times a given lhs occurs
prob=float(pcount[p]) / lcount[p.lhs()]) for p in pcount]
################################################################# # Parsing Grammars #################################################################
# Parsing CFGs
""" Return a list of context-free ``Productions``. """ return parse_production(input, standard_nonterm_parser)
""" Return the ``ContextFreeGrammar`` corresponding to the input string(s).
:param input: a grammar, either in the form of a string or as a list of strings. """
# Parsing Probabilistic CFGs
""" Return a list of PCFG ``WeightedProductions``. """ return parse_production(input, standard_nonterm_parser, probabilistic=True)
""" Return a probabilistic ``WeightedGrammar`` corresponding to the input string(s).
:param input: a grammar, either in the form of a string or else as a list of strings. """ probabilistic=True)
# Parsing Feature-based CFGs
""" Return a list of feature-based ``Productions``. """ return parse_production(input, fstruct_parser)
""" Return a feature structure based ``FeatureGrammar``.
:param input: a grammar, either in the form of a string or else as a list of strings. :param features: a tuple of features (default: SLASH, TYPE) :param logic_parser: a parser for lambda-expressions, by default, ``LogicParser()`` :param fstruct_parser: a feature structure parser (only if features and logic_parser is None) """
logic_parser=logic_parser) elif logic_parser is not None: raise Exception('\'logic_parser\' and \'fstruct_parser\' must ' 'not both be set')
# Parsing generic grammars
""" Parse a grammar rule, given as a string, and return a list of productions. """
# Parse the left-hand side.
# Skip over the arrow.
# Parse the right hand side. # Probability. raise ValueError('Production probability %f, ' 'should not be greater than 1.0' % (probabilities[-1],))
# String -- add terminal.
# Vertical bar -- start new rhside.
# Anything else -- nonterminal. else:
for (rhs, probability) in zip(rhsides, probabilities)] else:
""" Return a pair consisting of a starting category and a list of ``Productions``.
:param input: a grammar, either in the form of a string or else as a list of strings. :param nonterm_parser: a function for parsing nonterminals. It should take a ``(string, position)`` as argument and return a ``(nonterminal, position)`` as result. :param probabilistic: are the grammar rules probabilistic? :type probabilistic: bool """ else:
continue_line = line[:-1].rstrip()+' ' continue raise ValueError('Bad argument to start directive') else: raise ValueError('Bad directive') else: # expand out the disjunctions on the RHS raise ValueError('Unable to parse line %s: %s\n%s' % (linenum+1, line, e))
raise ValueError('No productions found!')
+ string[pos:])
################################################################# # Parsing Dependency Grammars #################################################################
('[^']+')\s* # single-quoted lhs (?:[-=]+>)\s* # arrow (?:( # rhs: "[^"]+" # doubled-quoted terminal | '[^']+' # single-quoted terminal | \| # disjunction ) \s*) # trailing space *$''', # zero or more copies re.VERBOSE)
except ValueError: raise ValueError('Unable to parse line %s: %s' % (linenum, line)) raise ValueError('No productions found!')
raise ValueError('Bad production string') else:
################################################################# # Demonstration #################################################################
""" A demonstration showing how ``ContextFreeGrammars`` can be created and used. """
from nltk import nonterminals, Production, parse_cfg
# Create some nonterminals S, NP, VP, PP = nonterminals('S, NP, VP, PP') N, V, P, Det = nonterminals('N, V, P, Det') VP_slash_NP = VP/NP
print('Some nonterminals:', [S, NP, VP, PP, N, V, P, Det, VP/NP]) print(' S.symbol() =>', repr(S.symbol())) print()
print(Production(S, [NP]))
# Create some Grammar Productions grammar = parse_cfg(""" S -> NP VP PP -> P NP NP -> Det N | NP PP VP -> V NP | VP PP Det -> 'a' | 'the' N -> 'dog' | 'cat' V -> 'chased' | 'sat' P -> 'on' | 'in' """)
print('A Grammar:', repr(grammar)) print(' grammar.start() =>', repr(grammar.start())) print(' grammar.productions() =>', end=' ') # Use string.replace(...) is to line-wrap the output. print(repr(grammar.productions()).replace(',', ',\n'+' '*25)) print()
S -> NP VP [1.0] NP -> Det N [0.5] | NP PP [0.25] | 'John' [0.1] | 'I' [0.15] Det -> 'the' [0.8] | 'my' [0.2] N -> 'man' [0.5] | 'telescope' [0.5] VP -> VP PP [0.1] | V NP [0.7] | V [0.2] V -> 'ate' [0.35] | 'saw' [0.65] PP -> P NP [1.0] P -> 'with' [0.61] | 'under' [0.39] """)
S -> NP VP [1.0] VP -> V NP [.59] VP -> V [.40] VP -> VP PP [.01] NP -> Det N [.41] NP -> Name [.28] NP -> NP PP [.31] PP -> P NP [1.0] V -> 'saw' [.21] V -> 'ate' [.51] V -> 'ran' [.28] N -> 'boy' [.11] N -> 'cookie' [.12] N -> 'table' [.13] N -> 'telescope' [.14] N -> 'hill' [.5] Name -> 'Jack' [.52] Name -> 'Bob' [.48] P -> 'with' [.61] P -> 'under' [.39] Det -> 'the' [.41] Det -> 'a' [.31] Det -> 'my' [.28] """)
""" A demonstration showing how a ``WeightedGrammar`` can be created and used. """
from nltk.corpus import treebank from nltk import treetransforms from nltk import induce_pcfg from nltk.parse import pchart
pcfg_prods = toy_pcfg1.productions()
pcfg_prod = pcfg_prods[2] print('A PCFG production:', repr(pcfg_prod)) print(' pcfg_prod.lhs() =>', repr(pcfg_prod.lhs())) print(' pcfg_prod.rhs() =>', repr(pcfg_prod.rhs())) print(' pcfg_prod.prob() =>', repr(pcfg_prod.prob())) print()
grammar = toy_pcfg2 print('A PCFG grammar:', repr(grammar)) print(' grammar.start() =>', repr(grammar.start())) print(' grammar.productions() =>', end=' ') # Use string.replace(...) is to line-wrap the output. print(repr(grammar.productions()).replace(',', ',\n'+' '*26)) print()
# extract productions from three trees and induce the PCFG print("Induce PCFG grammar from treebank data:")
productions = [] for item in treebank.items[:2]: for tree in treebank.parsed_sents(item): # perform optional tree transformations, e.g.: tree.collapse_unary(collapsePOS = False) tree.chomsky_normal_form(horzMarkov = 2)
productions += tree.productions()
S = Nonterminal('S') grammar = induce_pcfg(S, productions) print(grammar) print()
print("Parse sentence using induced grammar:")
parser = pchart.InsideChartParser(grammar) parser.trace(3)
# doesn't work as tokens are different: #sent = treebank.tokenized('wsj_0001.mrg')[0]
sent = treebank.parsed_sents('wsj_0001.mrg')[0].leaves() print(sent) for parse in parser.nbest_parse(sent): print(parse)
import nltk.data g = nltk.data.load('grammars/book_grammars/feat0.fcfg') print(g) print()
""" A demonstration showing the creation and inspection of a ``DependencyGrammar``. """ grammar = parse_dependency_grammar(""" 'scratch' -> 'cats' | 'walls' 'walls' -> 'the' 'cats' -> 'the' """) print(grammar)
""" A demonstration of how to read a string representation of a CoNLL format dependency tree. """ dg = DependencyGraph(""" 1 Ze ze Pron Pron per|3|evofmv|nom 2 su _ _ 2 had heb V V trans|ovt|1of2of3|ev 0 ROOT _ _ 3 met met Prep Prep voor 8 mod _ _ 4 haar haar Pron Pron bez|3|ev|neut|attr 5 det _ _ 5 moeder moeder N N soort|ev|neut 3 obj1 _ _ 6 kunnen kan V V hulp|ott|1of2of3|mv 2 vc _ _ 7 gaan ga V V hulp|inf 6 vc _ _ 8 winkelen winkel V V intrans|inf 11 cnj _ _ 9 , , Punc Punc komma 8 punct _ _ 10 zwemmen zwem V V intrans|inf 11 cnj _ _ 11 of of Conj Conj neven 7 vc _ _ 12 terrassen terras N N soort|mv|neut 11 cnj _ _ 13 . . Punc Punc punt 12 punct _ _ """) tree = dg.tree() print(tree.pprint())
cfg_demo() pcfg_demo() fcfg_demo() dg_demo() sdg_demo()
demo()
'Production', 'DependencyProduction', 'WeightedProduction', 'ContextFreeGrammar', 'WeightedGrammar', 'DependencyGrammar', 'StatisticalDependencyGrammar', 'induce_pcfg', 'parse_cfg', 'parse_cfg_production', 'parse_pcfg', 'parse_pcfg_production', 'parse_fcfg', 'parse_fcfg_production', 'parse_grammar', 'parse_production', 'parse_dependency_grammar', 'parse_dependency_production', 'demo', 'cfg_demo', 'pcfg_demo', 'dg_demo', 'sdg_demo', 'toy_pcfg1', 'toy_pcfg2']
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