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AI - Weeks 19
Natural Language
Processing PART 2
Lee McCluskey, room 2/07
Email [email protected]
http://scom.hud.ac.uk/scomtlm/cha2555/
Natural Language Processing
NLP: the process
Text (sentence, email, news story..)
-- Parsing
-- Referencing
UNDERSTANDING PROCESS
(“Natural Language Understanding”)
-- Meaning
Extraction and
Integration
Knowledge Base: representation of meaning
Summary/
Classification
Translation
Natural
Language
Generation
Natural Language Processing
NLP: the process
Text
“The cat sits on the mat”
sentence
UNDERSTANDING PROCESS
(“Natural Language Understanding”)
np
The cat
Knowledge Base: representation of meaning
Fact(type: statement,
agent: Fido,
action: is_a,
object: cat)
Fact(type: statement,
agent: Freda,
action: loves,
object: Fido)
Natural Language Processing
vp
sits on the mat
Fact(type: statement,
agent: cat-002,
action: sits_on,
object: mat-001)
NLP (NLU) : typical process
1.
2.
3.
4.
5.
6.
Scanning
Parsing
Finding referents for pronouns etc
Resolving Ambiguities
Meaning Extraction
Meaning Integration
Natural Language Processing
NLP (NLU) : tools to help
• Parser- Generators (e.g. YACC, JavaCUP) are tools
which input BNF Grammars and output Parsers for
computer languages such as programming languages.
• Extra information can be added to the Grammar to
make the Parser output useful information.
• PGs can be used for Natural Language Processing also.
Grammar
Sentence
/ program
Parser Generator
Parser
Parse Tree or Syntax
Error Report
Natural Language Processing
NLP (NLU) : Definite Clause Grammars
Prolog has a built in Parser Generator tool called the
“Definite clause grammar”
See
http://en.wikipedia.org/wiki/Definite_clause_grammar
http://www.cs.sunysb.edu/~warren/xsbbook/node10.html
This interprets grammar rules as “recursive descent” parsers (hence generating a
parser immediately from the grammar).
DCG - very simple example – here is a BNF grammar:
<sentence> --> <noun> <verb> <noun>
<noun> --> i | sentences
<verb> --> parse
Natural Language Processing
NLP (NLU) : Definite Clause Grammars
Grammar with this Prolog-looking syntax
sentence
--> noun, verb, noun.
noun --> [i].
noun --> [sentences].
verb --> [parse].
Input this to the Prolog Interpreter gives a listing of:
sentence(A, B) :noun(A, C),
verb(C, D),
noun(A, B) :A = [ i | B].
noun(A, B) :A = [sentences | B].
verb(A, B) :A = [ parse | B ].
noun(D, B).
Try it out with sentence([i,parse,sentences],A).
Natural Language Processing
Larger Example – BNF grammar for a bit of English
sentence -->
noun_phrase -->
noun_phrase -->
noun_phrase -->
noun_phrase -->
verb_phrase -->
verb_phrase -->
determiner
-->
adjective -->
noun
-->
noun
-->
verb
-->
preposition -->
noun_phrase verb_phrase
determiner adjective noun
adjective noun
determiner noun
noun
verb noun_phrase
verb preposition noun_phrase
a | an
fruit
flies | fruit | time | arrow
banana
like | flies
like
Natural Language Processing
Example in Prolog DCG syntax
sentence
-->
noun_phrase -->
noun_phrase -->
noun_phrase -->
verb_phrase -->
verb_phrase -->
determiner -->
adjective
-->
noun
-->
noun
-->
noun
-->
noun
-->
noun
-->
verb
-->
verb
-->
preposition -->
noun_phrase, verb_phrase.
determiner, adjective, noun.
adjective, noun.
determiner, noun.
verb, noun_phrase.
verb, preposition, noun_phrase.
[a].
[fruit].
[flies].
This Grammar can
[banana].
[fruit].
now be loaded into
[time].
Prolog and ACTS
[arrow].
LIKE A PARSER.
[like].
[flies].
[like].
Natural Language Processing
Prolog Grammar Rules
sentence(A, B) :noun_phrase(A, C),
verb_phrase(C, B).
noun_phrase(A, B) :determiner(A, C), adjective(C, D), noun(D, B).
noun_phrase(A, B) :adjective(A, C), noun(C, B).
noun_phrase(A, B) :determiner(A, C), noun(C, B).
verb_phrase(A, B) :verb(A, C), noun_phrase(C, B).
verb_phrase(A, B) :verb(A, C), preposition(C, D), noun_phrase(D, B).
determiner(A,B) :- A = [a|B].
adjective(A,B) :- A = [fruit| B].
noun(A,B) :- A = [flies|B].
noun(A,B) :- A = [banana|B].
This is the Prolog
noun(A,B) :- A= [fruit|B].
Code that the
noun(A,B) :- A = [time|B].
Grammar Translates
noun(A,B) :- A = [arrow|B].
verb(A,B) :- A = [like|B].
to. The variables
verb(A,B) :- A = [flies|B].
implement a kind of
preposition(A,B) :- A = [like|B].
“stream processing”
Natural Language Processing
Getting More From the Parsing Stage
Other functions we might need – extract information about the parse,
and ensure constraints are maintained in various parts of the
sentence, eg
- Return parse tree
- Check consistency of gender
- Checking consistency of number
sentence(sentence( NP, VP)) -->
noun_phrase(NP, No, Gender),
verb_phrase(VP, No, Gender).
-- build up parse tree as “self describing” term
-- when a part of the sentence commits to number or gender, then
record it for consistency
Natural Language Processing
NLP (NLU) : Definite Clause Grammars
Grammar with this Prolog-looking syntax
sentence(s(subject(S),V,object(O)))
--> noun(S), verb(V), noun(O).
noun(noun(i)) --> [i].
noun(noun(sentence)) --> [sentences].
verb(verb(parse)) --> [parse].
Input this to the Prolog Interpreter gives a listing of:
sentence(s(subject(S), V, object(O)), A, B) :noun(S, A, C),
verb(V, C, D),
noun(O, D, B).
noun(noun(i), A, B) :A = [ i | B].
noun(noun(sentence), A, B) :A = [sentences | B].
verb(verb(parse), A, B) :A = [ parse | B ].
Try it out sentence(Tree, [i,parser,sentences],X).
X = [],
Tree = s(subject(noun(i)),verb(parser),object(noun(sentence))) ? yes
Natural Language Processing
Parsing + Returning a Parse Tree
/* syntax bit + No (-singular or plural)
+ Gender (-Masc, Fem or Inamin.)*/
sentence(sentence( NP, VP)) -->
noun_phrase(NP, No, Gender),
verb_phrase(VP, No, Gender).
noun_phrase(noun_phrase([D,N]), No,Gender) -->
d(D, No,Gender),
n(N, No,Gender).
verb_phrase(verb_phrase([V,N]), No,Gender) -->
v(V, No,Gender),
noun_phrase(N, _,_). /* no ref to no
or gen of object*/
verb_phrase(verb_phrase([V]), No,Gender) -->
v(V, No,Gender).
d(determiner(the), No,Gender) -->
[the].
d(determiner(a), singular,Gender) -->
[a].
d(determiner(some), plural,Gender) --> [some].
sentence(X,[the,man,eats,the,apples],Y).
d(determiner(all), plural,Gender) -->
[all].
n(noun(apple), singular, inanimate) --> [apple].
X = sentence(
n(noun(apples), plural, inanimate) --> [apples].
noun_phrase([determiner(the),noun(man)]),
n(noun(man), singular, animate) --> [man].
verb_phrase([verb(eat),
n(noun(men), plural, animate) --> [men].
noun_phrase([determiner(the),noun(apples)])])),
v(verb(eat), singular, animate) --> [eats].
Y = [] ?
v(verb(eats), plural, animate) --> [eat].
v(verb(sing), singular, animate) --> [sings].
Natural Language Processing
v(verb(sings), plural, animate) --> [sing].