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Transcript
NLP: Parsing and more
Grammar
Topics:
DCG recognisor
• two implementations
Parsing
• Parse tree
• DCG recognisor with grammar features
A Simple Grammar
S  NP VP
VP  V NP
NP  Proper_N
NP  det N
Proper_N  John
Proper_N  Mary
N  cake
V  loves
V  ate
det  the
Sentences in this language:
“John loves Mary”
“John ate the cake”
“John loves the cake”
Definite Clause Grammars
(DCGs)
The above grammar can be simply
implemented in DCG notation as follows:
s --> np, vp.
vp --> v, np.
np --> proper_n.
np --> det, n.
proper_n --> [john].
proper_n --> [mary].
n --> [cake].
v --> [loves].
v --> [ate].
det --> [the].
Translating DCG
Consider the rule
s --> np, vp.
Prolog translates this as:
s(Ws1,Ws2) :- np(Ws1,Ws),vp(Ws,Ws2).
This says that after taking an s off the start of
Ws1, Ws2 remains
The rule
proper_n --> [john].
is translated as
proper_n([john|Ws],Ws).
Query
• s([john, ate, the cake],[]).
• Yes
• s([ate, john, cake, the],[]).
• No
A Second Implementation
A more efficient implementation:
s --> np, vp.
vp --> [V],{verb(V)},np.
np --> [N],{proper_n(N)}.
np --> [Det],{det(Det)},
[N],{noun(N)}.
proper_n(john).
proper_n(mary).
noun(cake).
verb(loves).
verb(ate).
det(the).
Notes:
1. The {} allow Prolog code to be embedded
in DCG rules
2. The cost of processing is now less
dependent on lexicon size (given good
indexing)
3. So far we have implemented only a DCG
recogniser, not a parser.
Parsing
Consider the goal
s([john,ate,the,cake],[])
It will have the following parse/proof tree
s
np
vp
proper_n
v
[john]
[ate]
np
det
n
[the]
[cake]
How to represent a tree in Prolog?
A DCG Parser
We can include extra arguments on nonterminals in our grammar, these allow us to
record the parse tree:
s(s(NP,VP)) -->
np(NP), vp(VP).
vp(vp(verb(V), NP)) -->
[V], {verb(V)}, np(NP).
np(np(proper_n(N))) -->
[N], {proper_n(N)}.
np(np(det(Det), noun(N))) -->
[Det], {det(Det)}, [N],
{noun(N)}.
A DCG Parser (ctd.)
Arguments to DCG non-terminals are
expanded by Prolog like this:
s(s(NP,VP),Ws1,Ws2) :np(NP,Ws1,Ws),vp(VP,Ws,Ws2).
Here, arguments are used to build up a parse
tree:
?- s(Parse, [john,ate,the,cake], []).
Parse = s(np(proper_n(john)),
vp(verb(ate),
np(det(the),
noun(cake))))
Eliminating Left Recursion
Example with left recursion:
S  S, PP
S  NP, VP
Will get into infinite loop!
S
S
NP
PP
VP
Example with left recursion eliminated:
S
S
 S1, S-PP
S-PP  
S1
S-PP
S-PP  PP, S-PP
NP
VP PP S-PP
S1
 NP, VP

Here's how to get the same parse tree as in the
1st grammar, but using the 2nd grammar:
s(S) --> s1(S1), s_pp(S1,S).
s_pp(S,S) --> [].
s_pp(S0,S) --> pp(PP),
s_pp(s(S0,PP),S).
s1(s(NP,VP)) --> np(NP), vp(VP).
Grammatical vs
Ungrammatical sentences
ungrammatical (syntactically incorrect) sentences
–
–
–
–
–
The John eats the hamburger.
John eat the hamburger.
John died Mary.
A hostages ate the hamburgers.
Him ate him.
syntactically correct sentences:
–
–
–
–
–
John eats the hamburger.
The people eat the hamburgers.
Hostages eat hamburgers.
Hamburgers killed Jim.
Cholesterol killed Jim.
Some Grammatical Features.
We can use the idea of grammatical
features to solve this problem:
• Number: singular, plural: hamburger,
hamburgers
• Person: 1st, 2nd, or 3rd: eat, eats
• Proper noun: true or false: John,
hamburger
• Mass noun: true (bread) or false
(bun): compare “a bread” & “a bun”
• Transitivity: transitive or
intransitive: give, die
• Case: subjective (I, he, she, they),
objective (me, him, her, them)
Modifying a DCG to handle
case
subjective
objective
I
me
you
you
he
him
she
her
it
it
they
them
Examples
He saw her.
She saw him.
You gave it to me.
I gave them to you.
They gave it to them.
They gave them it.
s --> np_sub, vp.
vp --> v, np_obj.
vp --> v.
pp --> prep, np_obj.
np_obj -> pro_obj. np_obj -> det, n.
np_sub -> pro_sub. np_sub -> det, n.
pro_sub --> [i].
pro_sub --> [you].
pro_sub --> [he]. pro_sub --> [she].
pro_obj --> [me]. pro_obj --> [you].
pro_obj --> [him]. pro_obj --> [her].
Augmenting a DCG to handle
case
There are other grammatical features we need
to match, and if we keep making more
specialized grammar rules, we will end up
with exponential number of rules.
Alternative is to augment grammar.
s --> np(sub), vp.
vp --> v, np(obj).
vp --> v.
pp --> prep, np(obj).
np(Case) -> pro(Case).
np(_) --> det, n.
pro(Case) -> [Pro],{pro(Pro,Case)}.
% Lexical entries:
pro(i, sub).
pro(you, sub).
pro(he, sub).
pro(she, sub).
pro(me, obj).
pro(you, obj).
pro(him, obj). pro(her, obj).
Subject-verb agreement
In English, number and person of the subject
must agree with the verb:
“I am” / “she is” / “they are”
Person Number Pronoun Verb examples…
––––––––––––––––––––––––––––––––––––––––––
1st
sing
I
eat
am
have
2nd –
you
eat
are
have
3rd
sing
he/she/it eats is
has
1st
plur
we
eat
are
have
3rd
plur
they
eat
are
have
Implementing subject-verb
agreement
Can combine checking subject-verb agreement in
person/number with case checking:
% subject must agree with verb
s --> np(Per, Num, sub), vp(Per, Num).
% person and number of object doesn’t matter
vp(Per, Num) --> v(Per, Num), np(_, _, obj).
vp(Per, Num) --> v(Per, Num).
% look up V, retrieve its person and number
v(Per, Num) --> [V], {v(V, Per, Num)}.
% person, number and case comes from pronoun
np(Per, Num, Case) --> pro(Per, Num, Case).
% look up person, number and case of pronoun
pro(Per, Num, Case) -->
[Pro], {pro(Pro, Per, Num, Case)}.
% lexical entries
pro(she, second, sing, obj).
v(eats, third, sing).
Agreement for nouns &
determiners
Articles (a type of determiner) have restrictions
based on number and whether the noun is
mass or count
Article Number Def/Indef Example
–––––––––––––––––––––––––––––––––––––
a/an singular
indefinite a man saw …

plural
indefinite
men saw…
the singular
definite
the man saw …
the plural
definite
the men saw…
Mass nouns (bread, money, water) take no
article when used in the indefinite, and go
with a verb in the singular
Determiners
Determiners can be quite complicated: can
involve numbers (& many other things)
Definite
Indefinite
–––––––––––––––––––––––––––
the dog
a dog
the red dogs
blue dogs
the three dogs
three dogs
my uncle Bob’s friend’s dog
every dog
every pink large dog
all but three of the red dogs
Proper nouns take no determiners
Noun/determiner agreement
Mass nouns
Count nouns
––––––––––––––––––––––––––––––––––––
the bread tastes good. the loaf tastes good.
*a bread taste good.
(don’t use indef article with mass nouns)
bread tastes good.
a loaf tastes good.
*bread taste good
loaves taste good.
(mass nouns go with sing. verb)
*the three bread …
the three loaves cost $4
*three bread …
three loaves cost $4
(can’t use numbers with mass nouns)
the money is heavy.
money buys power.
the coins are heavy.
the coin is heavy.
a coin buys …
coins buy icecreams
DCG rules for
noun/determiner agreement
% Proper nouns are noun-phrases
np(Number, _Person, _Case) -->
proper_n(Number, _).
% Mass nouns need no determiners
np(sing, _Person, _Case) -->
n1(sing, mass).
% Determiner-Noun (can’t have indef
%
determiner + mass noun)
np(Number, _, _) -->
det(Number, Definite),
n1(Number, Mass),
{\+ (Mass=mass, Definite=indef)}.
n1(Number, Mass) -->
adj, n1(Number, Mass).
n1(Number, Mass) --> n(Number, Mass).
DCG rules for noun/
determiner agreement (ctd)
n(Number, Mass) -->
[N], {noun(N, Number, Mass)}.
proper_n(Number, Mass) -->
[N],{proper_noun(N, Number, Mass)}.
det(Number, Definite) -->
[], {det([], Number, Definite)}.
det(Number, Definite) -->
[Det], {det(Det, Number,
Definite)}.
adj --> [Adj], {adj(Adj)}.
proper_noun(john, sing, count).
noun(loaf, sing, count).
noun(loaves, plur, count).
noun(bread, sing, mass).
det(a, sing, indef).
det([], plur, indef).
det(the, _, def).
adj(three).
adj(large).