what is the “context” for contextual vocabulary acquisition? william j. rapaport department of...
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What Is the “Context” forContextual Vocabulary Acquisition?
William J. RapaportDepartment of Computer Science & Engineering
Department of Philosophy
Center for Cognitive Science
NSF ROLE Grant REC-0106338
Outline
• People can figure out a meaning for a word “from context”
• What does “context” mean in this context?
Definition of “CVA”
“Contextual Vocabulary Acquisition” =def
• the acquisition of word meanings from text– “incidental”
– “deliberate”
• by reasoning about– contextual cues
– background knowledge• Including prior word-meaning hypotheses, language knowledge…
• without external sources of help– no dictionaries
– no people
CVA: From Algorithm to Curriculum
1. Computational theory of CVA– Based on:
• algorithms developed by Karen Ehrlich (1995)• verbal protocols (case studies)
– Implemented in a semantic-network-basedknowledge-representation & reasoning system• SNePS (Stuart C. Shapiro & colleagues)
2. Educational curriculum to teach CVA– Based on our algorithms & protocols– To improve vocabulary & reading comprehension– Joint work with Michael Kibby
• Center for Literacy & Reading Instruction
People Do “Incidental” CVA
• We know more words than explicitly taught– Average high-school grad knows ~45K words learned ~2.5K words/year (over 18 yrs.)– But only taught ~400/school-year
• ~ 4800 in 12 years of school (~ 10% of total)
Most word meanings learned from context– “incidentally” (unconsciously)
• How?
People Also Do “Deliberate” CVA
• You’re reading;• You understand everything you read, until…• You come across a new word• Not in dictionary• No one to ask• So, you try to “figure out” its meaning from “context”• How?
– guess? derive? infer? deduce? educe? construct? predict? …
– our answer: Compute it! Via inferential search of “context”/KB
• But what KB?
CVA as Cognitive Science
• Studied in:– AI / computational linguistics– Psychology– Child-language development (L1 acquisition)– L2 acquisition (e.g., ESL)– Reading education (vocabulary development)
• Thus far: “multi-”disciplinary• Not yet: “inter-”disciplinary!
(From Malory’s 15th century Morte d’Arthur [page # in brackets])
1. There came a white hart running into the hall with a white brachet next to him, and thirty couples of black hounds came running after them. [66]
• People: brachet = animal? inanimate object? don’t know.
• Computer: brachet = physical object• (because only physical objects have color)
2. As the hart went by the sideboard, the white brachet bit him. [66]
• People: brachet = animal
• Computer: brachet = animal• (because only animals bite)
Malory, continued
3. The knight arose, took up the brachet and rode away with the brachet. [66]
• People: brachet = animal / small animal
• Computer: brachet = small animal• (because: picked up and carried)
4. A lady came in and cried aloud to King Arthur, “Sire, the brachet is mine”. [66]
• People: brachet = pet / small, valuable animal
• Computer: brachet = small, valuable animal• (because: what’s wanted is valuable)
Malory, continued
10. There was the white brachet which bayed at him fast. [72]
• People: brachet = dog
• Computer: brachet = hound (i.e., dog that hunts)• (because only hounds, which are hunting dogs, bay)
18. The hart lay dead; a brachet was biting on his throat, and other hounds came behind. [86]
• People: brachet = hound
• Computer: brachet = hound (i.e., dog that hunts)• (because “x and other y” x is a y)
How (Not) to Teach CVA:Vague Strategies
• Clarke & Nation 1980: a “strategy” (algorithm)1.Look at word & context; determine POS
2.Look at grammatical context• E.g., “who does what to whom”?
3.Look at wider context• [E.g., for clues re: causal, temporal, class-membership, etc.]
4.Guess the word; check your guess
Vague strategies:
• “guess the word”
=
“then a miracle occurs”
• Surely,
we computer scientists
can “be more explicit”!
A More Precise, Teachable Algorithm
• Treat “guess” as a procedure call– Fill in the details with our algorithm
• Convert the algorithm into a curriculum– To enhance students’ abilities to use deliberate
CVA strategies
Figure out meaning of word from what?
• context (i.e., the text)?– Werner & Kaplan 52, McKeown 85, Schatz & Baldwin 86
• context and reader’s background knowledge?– Granger 77, Sternberg 83, Hastings 94
• context including background knowledge?– Nation & Coady 88, Graesser & Bower 90
• Note:– “context” = text context is external to reader’s mind
• Could also be spoken/visual/situative (still external)
– “background knowledge”: internal to reader’s mind
• What is (or should be) the “context” for CVA?
Some Proposed Preliminary Definitions(to extract order out of confusion)
• Unknown word for a reader =def
– Word or phrase that reader has never seen before– Or only has vague idea of its meaning
• Different levels of knowing meaning of word
– Notation: “X”
Proposed preliminary definitions
• Text =def
– (written) passage – containing X– single phrase or sentence … several paragraphs
Proposed preliminary definitions
• Co-text of X in some text =def
– The entire text “minus” X; i.e., entire text surrounding X
– E.g., if X = ‘brachet’, and text =• “There came a white hart running into the hall with a white
brachet next to him, and thirty couples of black hounds came running after them.”
Then X’s co-text in this text =• “There came a white hart running into the hall with a white
______ next to him, and thirty couples of black hounds came running after them.”
– Cf. “cloze” tests in psychology• But, in CVA, reader seeks meaning or definition
– NOT a missing word or synonym: There’s no “correct” answer!
– “Co-text” is what many mean by “context”• BUT: they shouldn’t!
Proposed preliminary definitions
• The reader’s prior knowledge =def – the knowledge that the reader has when s/he
begins to read the text– and is able to recall as needed while reading
• “knight picks up & carries brachet” ? small
• Warnings:– “knowledge” truth
• so, “prior beliefs” is better
– “prior” vs. “background” vs. “world”, etc.• See next slide!
Proposed preliminary definitions
• Possible synonyms for “prior knowledge”, each with different connotation:
– Background knowledge:• Can use for information that author assumes reader to have
– World knowledge:• General factual knowledge about things other than the text’s topic
– Domain knowledge:• Specialized, subject-specific knowledge about the text’s topic
– Commonsense knowledge:• Knowledge “everyone” has
– E.g., CYC, “cultural literacy” (Hirsch)
• These overlap:– PK should include some CSK, might include some DK– BK might include much DK
Steps towards a
Proper Definition of “Context”• Step 1:
– The context of X for a reader =def
1. The co-text of X
2. “+” the reader’s prior knowledge
• Both are needed!– After reading:
• “the white brachet bit the hart in the buttock”
most subjects infer that brachets are (probably) animals, from:
• That text, plus:
• Available PK premise: “If x bites y, then x is (probably) an animal.
– Inference is not an enthymeme! (because …)
Proper definition of “context”:
• But (inference not an enthymeme because):– When you read, you “internalize” the text
• You “bring it into” your mind
• Gärdenfors 1997, 1999; Jackendoff 2002
– This “internalized text” is more important than the actual words on paper:• Text: “I’m going to put the cat out”
• Misread as: “I’m going to put the car out” – leads to different understanding of “the text”
– What matters is what the reader thinks the text is,• Not what the text actually is
• Therefore …
Proper definition of “context”:
• Step 2:
– The context of X for a reader =def
• A single KB, consisting of:
1. The reader’s internalized co-text of X
2. “+” the reader’s prior knowledge
Proper definition of “context”:
• But: What is “+”?– Not: mere conjunction or union!
– Active readers make inferences while reading.• From text = “a white brachet”
& prior commonsense knowledge = “only physical objects have color”,
reader might infer that brachets are physical objects
• From “The knight took up the brachet and rode away with the brachet.”
& prior commonsense knowledge about size,
reader might infer that brachet is small enough to be carried
– Whole > Σ parts:• inference from [internalized text + PK] new info not in text or in PK
• I.e., you can learn from reading!
Proper definition of “context”:
• But: Whole < Σ parts!– Reader can learn that some prior beliefs were mistaken
• Or: reader can decide that text is mistaken (less likely)
• Reading & CVA need belief revision!
• operation “+”: – input: PK & internalized co-text– output: “belief-revised integration” of input, via:
• Expansion:– addition of new beliefs from ICT into PK, plus new inferences
• Revision:– retraction of inconsistent prior beliefs together with inferences from them
• Consolidation:– eliminate further inconsistencies
B-R Integrated KB Text
PK1
PK2
PK3
PK4
T1
I(T1)
internalization
P5
inference
T2
I(T2)
P6
T3
I(T3)
P7
Note: All “contextual” reasoning is done in this “context”:
Proper definition of “context”:
• One more detail: X needs to be internalized• Context is a 3-place relation among:
– Reader, word, and text
• Final(?) def.:
– Let T be a text
– Let R be a reader of T
– Let X be a word in T (that is unknown to R)
– Let T-X be X’s co-text in T.
– Then:• The context that R should use to hypothesize a meaning
for R’s internalization of X as it occurs in T =def
– The belief-revised integration of R’s prior knowledge with R’s internalization of T-X.
This definition agrees with…
• Cognitive-science & reading-theoretic views of text understanding– Schank 1982, Rumelhart 1985, etc.
• & KRR techniques for text understanding:– Reader’s mind modeled by KB of prior knowledge
• Expressed in KR language (for us: SNePS)
– Computational cognitive agent reads the text,• “integrating” text info into its KB, and• making inferences & performing belief revision along the way
– When asked to define a word,• Agent deductively searches this single, integrated KB for
information to fill slots of a definition frame
– Agent’s “context” for CVA = this single, integrated KB
Distinguishing Prior Knowledge from Integrated Co-Text
• So KB can be “disentangled” as needed for belief revision or to control inference:
• Each proposition in the single, integrated KB is marked with its “source”:– Originally from PK– Originally from text– Inferred
• Sources of premises
Some Open Questions
• Roles of spoken/visual/situative contexts• Relation of CVA “context” to formal theories of
context (e.g., McCarthy, Guha…)
• Relation of I(T) to prior-KB; e.g.:– Is I(Ti) true in prior-KB?
• It is “accepted pro tem”.
– Is I(T) a “subcontext” of pKB or B-R KB?
• How to “activate” relevant prior knowledge.• Etc.
Summary
• People can figure out a meaning for a word “from context”, where…
• “Context” = belief-revised integration of:– reader’s prior knowledge, with – internalized information from the text
• This clearer concept of relevant notion of “context” will help us:– evaluate other research– develop our curriculum