nltk.grammar module¶
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 CFG
class is used to encode context free grammars. Each
CFG
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 CFG
, 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:
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.
- class nltk.grammar.CFG[source]¶
Bases:
object
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.
- __init__(start, productions, calculate_leftcorners=True)[source]¶
Create a new context-free grammar, from the given start state and set of
Production
instances.- Parameters
start (Nonterminal) – The start symbol
productions (list(Production)) – The list of productions that defines the grammar
calculate_leftcorners (bool) – False if we don’t want to calculate the leftcorner relation. In that case, some optimized chart parsers won’t work.
- classmethod binarize(grammar, padding='@$@')[source]¶
Convert all non-binary rules into binary by introducing new tokens. Example:
Original: A => B C D After Conversion: A => B A@$@B A@$@B => C D
- check_coverage(tokens)[source]¶
Check whether the grammar rules cover the given list of tokens. If not, then raise an exception.
- chomsky_normal_form(new_token_padding='@$@', flexible=False)[source]¶
Returns a new Grammar that is in chomsky normal
- Param
new_token_padding Customise new rule formation during binarisation
- classmethod eliminate_start(grammar)[source]¶
Eliminate start rule in case it appears on RHS Example: S -> S0 S1 and S0 -> S1 S Then another rule S0_Sigma -> S is added
- classmethod fromstring(input, encoding=None)[source]¶
Return the grammar instance corresponding to the input string(s).
- Parameters
input – a grammar, either in the form of a string or as a list of strings.
- is_binarised()[source]¶
Return True if all productions are at most binary. Note that there can still be empty and unary productions.
- is_chomsky_normal_form()[source]¶
Return True if the grammar is of Chomsky Normal Form, i.e. all productions are of the form A -> B C, or A -> “s”.
- is_flexible_chomsky_normal_form()[source]¶
Return True if all productions are of the forms A -> B C, A -> B, or A -> “s”.
- is_leftcorner(cat, left)[source]¶
True if left is a leftcorner of cat, where left can be a terminal or a nonterminal.
- Parameters
cat (Nonterminal) – the parent of the leftcorner
left (Terminal or Nonterminal) – the suggested leftcorner
- Return type
bool
- is_nonlexical()[source]¶
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.
- leftcorner_parents(cat)[source]¶
Return the set of all nonterminals for which the given category is a left corner. This is the inverse of the leftcorner relation.
- Parameters
cat (Nonterminal) – the suggested leftcorner
- Returns
the set of all parents to the leftcorner
- Return type
set(Nonterminal)
- leftcorners(cat)[source]¶
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)
- Parameters
cat (Nonterminal) – the parent of the leftcorners
- Returns
the set of all leftcorners
- Return type
set(Nonterminal)
- productions(lhs=None, rhs=None, empty=False)[source]¶
Return the grammar productions, filtered by the left-hand side or the first item in the right-hand side.
- Parameters
lhs – Only return productions with the given left-hand side.
rhs – Only return productions with the given first item in the right-hand side.
empty – Only return productions with an empty right-hand side.
- Returns
A list of productions matching the given constraints.
- Return type
list(Production)
- classmethod remove_unitary_rules(grammar)[source]¶
Remove nonlexical unitary rules and convert them to lexical
- class nltk.grammar.DependencyGrammar[source]¶
Bases:
object
A dependency grammar. A DependencyGrammar consists of a set of productions. Each production specifies a head/modifier relationship between a pair of words.
- __init__(productions)[source]¶
Create a new dependency grammar, from the set of
Productions
.- Parameters
productions (list(Production)) – The list of productions that defines the grammar
- class nltk.grammar.DependencyProduction[source]¶
Bases:
Production
A dependency grammar production. Each production maps a single head word to an unordered list of one or more modifier words.
- class nltk.grammar.Nonterminal[source]¶
Bases:
object
A non-terminal symbol for a context free grammar.
Nonterminal
is a wrapper class for node values; it is used byProduction
objects to distinguish node values from leaf values. The node value that is wrapped by aNonterminal
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. TwoNonterminals
are considered equal if their symbols are equal.- See
CFG
,Production
- Variables
_symbol – The node value corresponding to this
Nonterminal
. This value must be immutable and hashable.
- class nltk.grammar.PCFG[source]¶
Bases:
CFG
A probabilistic context-free grammar. A PCFG consists of a start state and a set of productions with probabilities. The set of terminals and nonterminals is implicitly specified by the productions.
PCFG productions use the
ProbabilisticProduction
class.PCFGs
impose the constraint that the set of productions with any given left-hand-side must have probabilities that sum to 1 (allowing for a small margin of error).If you need efficient key-based access to productions, you can use a subclass to implement it.
- Variables
EPSILON – The acceptable margin of error for checking that productions with a given left-hand side have probabilities that sum to 1.
- EPSILON = 0.01¶
- __init__(start, productions, calculate_leftcorners=True)[source]¶
Create a new context-free grammar, from the given start state and set of
ProbabilisticProductions
.- Parameters
start (Nonterminal) – The start symbol
productions (list(Production)) – The list of productions that defines the grammar
calculate_leftcorners (bool) – False if we don’t want to calculate the leftcorner relation. In that case, some optimized chart parsers won’t work.
- Raises
ValueError – if the set of productions with any left-hand-side do not have probabilities that sum to a value within EPSILON of 1.
- class nltk.grammar.ProbabilisticProduction[source]¶
Bases:
Production
,ImmutableProbabilisticMixIn
A probabilistic context free grammar production. A PCFG
ProbabilisticProduction
is essentially just aProduction
that has an associated probability, which represents how likely it is that this production will be used. In particular, the probability of aProbabilisticProduction
records the likelihood that its right-hand side is the correct instantiation for any given occurrence of its left-hand side.- See
Production
- __init__(lhs, rhs, **prob)[source]¶
Construct a new
ProbabilisticProduction
.- Parameters
lhs (Nonterminal) – The left-hand side of the new
ProbabilisticProduction
.rhs (sequence(Nonterminal and terminal)) – The right-hand side of the new
ProbabilisticProduction
.prob – Probability parameters of the new
ProbabilisticProduction
.
- class nltk.grammar.Production[source]¶
Bases:
object
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 andNonterminals
.) “terminals” can be any immutable hashable object that is not aNonterminal
. Typically, terminals are strings representing words, such as"dog"
or"under"
.- See
CFG
- See
DependencyGrammar
- See
Nonterminal
- Variables
_lhs – The left-hand side of the production.
_rhs – The right-hand side of the production.
- __init__(lhs, rhs)[source]¶
Construct a new
Production
.- Parameters
lhs (Nonterminal) – The left-hand side of the new
Production
.rhs (sequence(Nonterminal and terminal)) – The right-hand side of the new
Production
.
- is_lexical()[source]¶
Return True if the right-hand contain at least one terminal token.
- Return type
bool
- is_nonlexical()[source]¶
Return True if the right-hand side only contains
Nonterminals
- Return type
bool
- nltk.grammar.induce_pcfg(start, productions)[source]¶
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 sidecount(A -> *)- Parameters
start (Nonterminal) – The start symbol
productions (list(Production)) – The list of productions that defines the grammar
- nltk.grammar.nonterminals(symbols)[source]¶
Given a string containing a list of symbol names, return a list of
Nonterminals
constructed from those symbols.- Parameters
symbols (str) – The symbol name string. This string can be delimited by either spaces or commas.
- Returns
A list of
Nonterminals
constructed from the symbol names given insymbols
. TheNonterminals
are sorted in the same order as the symbols names.- Return type
list(Nonterminal)
- nltk.grammar.read_grammar(input, nonterm_parser, probabilistic=False, encoding=None)[source]¶
Return a pair consisting of a starting category and a list of
Productions
.- Parameters
input – a grammar, either in the form of a string or else as a list of strings.
nonterm_parser – a function for parsing nonterminals. It should take a
(string, position)
as argument and return a(nonterminal, position)
as result.probabilistic (bool) – are the grammar rules probabilistic?
encoding (str) – the encoding of the grammar, if it is a binary string