Transcript Norms and Exploitations

Syntagmatic Preferences
Patrick Hanks
Masaryk University
In honour of Yorick Wilks
BCS, London, June 22, 2007
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What's so important about
“My car drinks gasoline”?
• Violation of “selection restrictions” is normal.
• So selectional restrictions aren't restrictions at all
– They are, in fact selectional preferences
– Different combinations of selectional preferences
activate different senses
• Yorick's insights of the 1970s deserve to be followed up
more vigorously and systematically than they have been.
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A language is a double helix
• Start from the bottom up:
– Let’s look at what the words do.
– How do people use words to make meanings?
• A natural language is a system of norms and exploitations:
– Norms: Animals drink water, people drink beverages
– Exploitations: My car drinks gasoline
• Syntagmatic rules governing normal linguistic behaviour
systematically interact with exploitation rules governing
how those norms are exploited
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Patterns of linguistic behaviour
• Normal linguistic behaviour is highly patterned.
• Words in isolation have meaning potential, not meaning
– A meaning potential is a more or less vague cluster of possibilities – e.g.
what does fire mean?
– A burning process? (and if so is it a good thing – in a house, under control – or a
bad thing, raging out of control in a forest?) An electric heater? A sense of
enthusiasm? Dismiss from employment? Operate a gun? Shoot an arrow? Cause
to enthuse? Bake?
– All of these and more.
– Much overlap.
– Sense enumeration doesn’t get it (cf Pustejovsky’s lexical conceptual paradigms)
• In context, the range of possible interpretations of a word is severely limited:
– People firing guns, ideas that fire people with enthusiasm, employers firing their
staff, firing pottery in a kiln
Word Use, Meaning, and
Linguistic Theory
• The normal uses of a word can be grouped into patterns, and meanings can
be associated with the patterns (rather than the word in isolation)
• So far they haven’t been. Why not?
– Lack of evidence
• Lexical analysis can only be done effectively with large corpora
– Tradition and intuition
• direttissimo assaults on word meaning
• No one thought to go the long way round, via patterns
– The tyranny of “all and only”
• Lexicographers aimed to cover all possible uses, not just all normal uses
• NLP and linguistic theory focused on boundary cases
– Syntactocentrism in linguistic theory
• misses the point about syntagmatics
– Lack of a suitable theory
• Aha! Preference Semantics provides the basis for such a theory
• We should take PS seriously and ally it with other relevant theoretical work
(Wittgenstein, Putnam, Rosch, Sinclair, Hoey, Pustejovsky, …)
Why is a Pattern Dictionary
Necessary?
• Standard dictionaries do not provide the contexts
that distinguish one sense of a word from another.
– very poor syntagmatic information
– give equal prominence to normal and merely
possible senses
– definitions (and senses) are not mutually exclusive
• WordNet: synsets ≠ word senses!
• FrameNet: frames ≠ word senses!
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Identifying norms is hard
• ... and boring
– The painful rediscovery of the obvious,
– which is only obvious when pointed out
• Only by painstaking corpus analysis is identifying norms
possible.
• What counts as a normal use of any verb? – e.g. drink
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Norms for 'drink', v.
1.
55% [[Human]] drink [[{Liquid = Water} | Beverage]]
2.
4% [[Animal]] drink [[Liquid = Water]]
3.
39% [[Human]] drink [NO OBJ]
4.
1% [[Human]] drink [[Experience]] {in}
5.
1% [[Human]] drink ([[Liquid = Beverage]]) {up}
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Some Exploitations of 'drink'
A metaphor (or literary allusion):
• The child of a nonconformist father learnt to drink deep of
the Catholic tradition .
– Owen Chadwick, 1991. Michael Ramsey: a life.
A coercion:
• ` He knows them all , ' she says adoringly , ` and they all
drink shampoo -- nearly every night .
– The Guardian, 1989.
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How pervasive is ambiguity?
• Not as pervasive as you might think.
– If we attach meanings to patterns, not to words, most
“ambiguities” don't get a chance to rear their ugly heads.
• But here's one: He drank.
• Could be a null-object alternation of “he drank [[Beverage]]”
• or it could mean that he had a problem with alcohol (pattern 2)
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Getting the right level of
generalization is hard
“John fired at a line of stags”
• Corpus evidence shows that fire at does not prefer ANIM in
the prepositional object slot. Any PHYSOBJ will do.
• Building a pattern dictionary is a constant struggle to get
“the right level” (or at least an acceptable level ) of
generalization
• Art is required to choose a level.
• There are no right answers (no absolutes).
– But plenty of wrong ones!
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Semantic Types and
Semantic Roles
• fire at assigns the semantic role “Target” to
words of semantic type [[Physical Object]]
• Semantic types are the intrinsic prototypical
values of nouns – their essences
• Semantic roles are assigned by context
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Word Meaning: a complex
linguistic Gestalt
• In the mind of an English speaker, the verb land is
primed for any or all of the following:
– passengers land from a plane – the pilot lands the plane – the plane
lands – we landed at Heathrow – passengers land from a boat (but
more probably they are soldiers) – a commander lands his troops
(but not from a plane) – a boat lands its cargo – a trawler lands its
catch – an angler lands a fish – Yorick landed the role of Caliban –
He landed a job in Sheffield – someone else may land in trouble – or
be landed with a problem – and someone may even land a blow on
your nose
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Imposing order on chaos
In the Pattern Dictionary:
• Verbs are sorted into patterns
• Exploitations are flagged for later analysis
• Nouns (“lexical sets”) are clustered into an
ontology
• The ontology is “distorted” by usage
• Lexical sets “shimmer”
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Lexical Sets “shimmer”
• [[Human]] attend [[Event]]
– Lexical set [[Event]] = { meeting, conference, funeral, ceremony,
course, school, seminar, lecture, session, class, rally, dinner,
hearing, briefing, reception, workshop, wedding, inquest, summit,
concert, event, premiere, …}
• [[Human]] participate {in [[Event]]}
– Lexical set [[Event]] = {debate, election, exercise, coup,
demonstration, activity, process, conference, consultation,
selection, meeting, …}
• [[Human]] hail [[Event]]
– Lexical set [[Event]] = {victory, success, agreement, vote, opening,
development, result, start, resurgence, …}
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Patterns are contrastive
• 2% [[Human]] launch [[Boat]]
• 7% [[Human]] launch [[Projectile]]
• 58% [[Human | Institution]] launch [[Activity | Plan]]
• 24% [[Institution]] launch [[{Artifact = Product} |
{Activity = Service}]]
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What is a Pattern Dictionary?
• a inventory of all normal patterns of verb
use
– not all possible uses.
• an ontology of “shimmering” lexical sets
(clusters of nouns according to semantic
type and argument roles)
• an inventory of semantically motivated
syntagmatic distinctions
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Tools needed to build a Pattern
Dictionary
• A balanced corpus of the language (i.e. general language)
• A theory
– An initial lexical architecture that guides clustering
Wilks, Pustejovsky, Sinclair, …
– A lexical model that distinguishes norms from exploitations
• A methodology: Corpus Pattern Analysis
– Hanks 2004, Hanks and Pustejovsky 2005
– Including statistical corpus analysis
• Church and Hanks 1989, Kilgarriff et al. 2004, 2005
• A shallow ontology
– A hierarchical organization of semantic types, reflecting word
groupings, not scientific conceptualization of the universe
• A suite of corpus tools: Manatee, Bonito, Word Sketch Engine
• Kilgarriff, Rychlý
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CPA procedure
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•
•
•
•
Create a sample concordance (KWIC index) for a
word:
– 250 examples of actual uses of the word
Identify the typical syntagmatic patterns.
Assign each line of the sample to one of the
patterns.
Take further samples if necessary.
– Introspection is used to interpret data, but not
to create data.
Store the pattern in the entry manager.
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In CPA, every line in the
sample must be classified
The choices are:
• Norms
• Exploitations
• Alternations
• Names (Midnight Storm: name of a horse, not a storm)
• Mentions (to mention a word or phrase is not to use it)
• Errors (e.g. learned mistyped as leaned)
• Unassignables
– See Proceedings of the Eleventh EURALEX International
Congress, pages 105–116, Lorient, France, 2004.
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How normal are norms? How
frequent are exploitations?
• Roughly 75% of all clauses activate “primary norms”
• About 20% activate secondary norms
– including conventional metaphors
– and some expressions that may once have been
exploitations themselves
• About 4% of all clauses involve exploitations of various
sorts
– dynamic metaphors, other tropes, coercions, ellipsis, etc.
• About 1% of all clauses are unclassifiable
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Browsing and Feedback
• The English Pattern Dictionary
• http://nlp.fi.muni.cz/projects/cpa/
• Browse the first 50 verbs at https://apollo.fi.muni.cz:8007/
– Login and password are both “guest”
– Click on the pattern number to see the whole pattern
– Click on “lines” to see supporting corpus evidence
• 50 verb entries have been completed and released
– Feedback, please!
• 400 additional entries have been analysed, awaiting release
– A shallow ontology has been drafted and is being edited
– But not populated with nouns yet
– 6500 verbs remain to be analysed
• EPD will not include rare words like saltate or saccharify
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