Download Ambiguity

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Lexical Ambiguity
!
• Definition: a word belongs to two or more word (“part of speech”) classes
• Example: the round table (adjective), to round the corner (verb), dance in a
round (noun), come round and see us (adverb), he walked round the room
(preposition)
• Finite state grammars can be used for resolving lexical ambiguity
P.1
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Grammar: Simple Finite State Network
Det
0
Noun
1
Verb
2
Noun
Det
3
4
J
J
the:
Det (definite)
little:
Adj (size)
orange: Adj (colour)
Noun (fruit)
5
J
J
Adj
Adj
Lexicon:
!
ducks:
Noun (animal)
Verb (action)
swallow: Noun (animal)
Verb (action)
flies:
Noun (animal)
Verb (action)
P.2
Center for PersonKommunikation
Grammar: Simple Finite State Network
the
Det
orange
Noun
0
1
Verb
2
!
Noun
Det
3
4
J
J
orange
little
Adj
Lexicon:
the:
Det (definite)
little:
Adj (size)
orange: Adj (colour)
Noun (fruit)
5
J
J
Adj
ducks:
Noun (animal)
Verb (action)
swallow: Noun (animal)
Verb (action)
flies:
Noun (animal)
Verb (action)
P.3
Center for PersonKommunikation
Parsing with Finite State Grammar
“parse tree”
Det
Adj
Adj
Noun
Verb
the
little orange ducks swallow
(definite) size colur animal action
!
Noun
flies
animal
P.4
Center for PersonKommunikation
Finite State Grammar: Conclusion
!
• FSNs can resolve lexical ambiguities
• FSNs cannot assign actual structural descriptions to sentences. The generated
structures are “flat” describing simple paths through the network.
• FSNs only describe legal sequences of terminal symbols
(Note: In NLP, syntactic parsing is sometimes preceded by “POS-tagging” (or “Constraintgrammars), a preprocessor that resolves many lexical ambiguities. This speeds up syntactic
parsing. POS-tagging is normally based on trainable finite state machines).
P.5
Center for PersonKommunikation
Grammar: Simple Recursive Transition Network
(equivalent to fsn)
NP
!
VP
Equivalent BNF:
S:
Det
Noun
NP:
J
Adj
Verb
NP
VP:
S -> NP VP
NP ->Noun
NP -> Det Noun
NP -> AdjP Noun
NP -> Det AdjP Noun
AdjP -> Adj
AdjP-> adj AdjP
VP ->Verb
VP -> Verb NP
J
P.6
Center for PersonKommunikation
Parsing with Recursive Transition Network Grammar
Phrase Structure (“parse tree”)
!
S
VP
NP
NP
Det
Adj
Adj
Noun
Verb
Noun
the
little orange ducks swallow flies
(definite) size colour animal action animal
P.7
Center for PersonKommunikation
Structural Ambiguity
!
• Definition: a context-free grammar can assign two or more phrase structures
(“parse trees”) to one and the same sequence of terminal symbols (words or
word classes).
• In formal language theory often referred to as the grammar being ambiguous
(ambiguous vs. unambiguous grammars)
• Examples:
– old men and women
– time flies like an arrow
– I saw the man with the telescope
P.8
Center for PersonKommunikation
Structural Ambiguity 1
(ambiguous context-free grammars)
• S-> NP VP (PP)
Subject+Predicate+a facultative prepositional phrase
describing e.g. instrument/time/place of the SubjectPredicate relation
•
•
•
•
I/me/him...
NP->Pron
NP->(Det) Noun (PP)
VP->Verb (NP)
PP-> Prep NP
!
(the/a) man (in England/round the corner/with a hat)
eat (sth.)/see (sth.)
in England/round the corner/with a hat/with a telescope
P.9
Center for PersonKommunikation
Structural Ambiguity 2
Phrase Structure 1.
!
S
NP
VP
NP
PP
NP
Pron
I
Verb
saw
Det
the
Noun
man
Prep
with
Det
a
Noun
telescope
P.10
Center for PersonKommunikation
Structural Ambiguity 3
Phrase Structure 2.
!
S
NP
VP
PP
NP
NP
Pron
I
Verb
saw
Det
the
Noun
man
Prep
with
Det
a
Noun
telescope
P.11
Center for PersonKommunikation
Context-free Grammar: Conclusion
!
• Like FSNs, RTNs/BNFs can resolve lexical ambiguities
• Additionally, RTNs/BNFs can assign actual structural descriptions to
sentences. The generated structures analyses the sentence into constituents.
• A proper constituent analysis is a vital step towards an actual semantic
interpretation of the sentence
In NLP, unification-based context-free grammars are often preferred because they can be
used with a number of efficient parsing algorithms developed in formal-language theory.
In general, such unification-grammars presuppose
• general parsing algorithms (no restrictions as regards left-recursion/right-recursion etc.)
• exhaustive parsing algorithms (because of ambiguities)
Widespread are algorithms derived from the Earley chart parsing algorithm (cf. J. Earley).
Example at http://www.sil.org/pcpatr/
P.12
Center for PersonKommunikation
More about Ambiguity 1.
!
• How do humans resolve ambiguities?
– Pragmatics:
• Understanding intentions
• World-knowledge
• Example:
– "Denmark will have a distinguished visit next year. The Russian president Boris
Jeltsin and the American president Bill Clinton will attend a meeting on social
problems in Copenhagen"
Translated from Danish:
"Danmark får fornemt besøg næste år. Den russiske præsident Boris Jeltsin og den
amerikanske præsident Bill Clinton skal til møde om sociale problemer i København"
P.13
Center for PersonKommunikation
More about Ambiguity 2.
!
• How are ambiguities resolved in NLP applications?
– Implementation of less ambiguous domain-specific sub-grammars
– Application of preference rules.
– In spoken dialogue systems:
• Implementation of system-directed dialogues (system-prompts)
• Clarification sub-dialogues
P.14
Center for PersonKommunikation
Exercise 1
• Consider the sentence
– I saw him with a telescope
Is this sentence ambiguous according to the grammar on slide 9?
• It has been argued that a more “correct” name for the word class “pronoun”
(e.g. I, him) would be “pronounphrase”. Elaborate on that based on the
example/grammar above
P.15
Center for PersonKommunikation
Exercise 2
• Do you know of anything that can be compared to “lexical ambiguity” in
high level programming languages?
• Could we in C, theoretically, collapse the assignment and expression symbols
(‘=‘, ‘==‘) into one symbol?
• Some C-compilers generate warnings on cases like
– int x=1,y=2;
– if (x=y) {/*do something*/}
Should they do that?
P.16
Center for PersonKommunikation
Exercise 3
• Download and install the CPK NLP Suite:
– www.cpk.auc.dk/~tb/nlpsuite
and join the “quick tour” through the programs.
Try the Winograd and Earley examples:
apspars -T wino1.aps wino1.snt
apspars -T wino2.aps wino2.snt
psgpars -T earley.psg earley.snt
Impatient people can read about the aps (Augmented Phrase Structure)
grammar format on www.cpk.auc.dk/~tb/articles/mmuirp98_7.htm
P.17