What Is the Context for Contextual Vocabulary Acquisition

What Is the “Context” for Contextual Vocabulary Acquisition? William J. Rapaport Department 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-based knowledge-representation & reasoning system • SNe. PS (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 ~45 K words learned ~2. 5 K 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? 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 (L 1 acquisition) – L 2 acquisition (e. g. , ESL) – Reading education (vocabulary development) • Thus far: “multi-”disciplinary • Not yet: “inter-”disciplinary!

What does ‘brachet’ mean?

(From Malory’s 15 th 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: Computer: • brachet = animal? inanimate object? don’t know. brachet = physical object (because only physical objects have color) 2. As the hart went by the sideboard, the white brachet bit him. [66] • • People: 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: Computer: • 4. brachet = animal / small animal brachet = small animal (because: picked up and carried) A lady came in and cried aloud to King Arthur, “Sire, the brachet is mine”. [66] • • People: Computer: • brachet = pet / small, valuable animal 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: Computer: • brachet = dog 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: 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, Mc. Keown 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: • Misread as: “I’m going to put the cat out” “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

Prior Knowledge PK 1 PK 2 PK 3 PK 4 Text

Prior Knowledge PK 1 PK 2 PK 3 PK 4 Text T 1

Integrated KB internalization PK 1 PK 2 PK 3 PK 4 Text I(T 1) T 1

B-R Integrated KB internalization PK 1 PK 2 I(T 1) inference PK 3 PK 4 Text P 5 T 1

B-R Integrated KB internalization PK 1 PK 2 I(T 1) inference PK 3 Text P 5 PK 4 I(T 2) P 6 T 1 T 2

B-R Integrated KB internalization PK 1 PK 2 Text I(T 1) T 1 T 2 inference PK 3 P 5 PK 4 I(T 2) P 6 I(T 3) T 3

B-R Integrated KB internalization PK 1 PK 2 Text I(T 1) T 1 T 2 inference PK 3 P 5 PK 4 I(T 2) P 6 I(T 3) T 3

Note: All “contextual” reasoning is done in this “context”: B-R Integrated KB internalization PK 1 P 7 PK 2 Text I(T 1) T 1 T 2 inference PK 3 P 5 PK 4 I(T 2) P 6 I(T 3) T 3

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: SNe. PS) – 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. , Mc. Carthy, 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 p. KB 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