Deictic Centers & Cognitive Structure in Narrative: Interdisciplinary Approach, Slides of Advanced Computer Architecture

Download Deictic Centers & Cognitive Structure in Narrative: Interdisciplinary Approach and more Slides Advanced Computer Architecture in PDF only on Docsity! Deictic Centers and Cognitive Structure of Narrative Comprehension Docsity.com Interdisciplinary Cognitive- Science • AI • cognitive psychology • education • geography • communicative disorders • linguistics • literary theory & practice • philosophy Docsity.com Understanding a Narrative (cont’d) b) Semantic (open-text, constructive) view: :-) • Reader constructs mental-model meaning (= theory) from narrative text (= data) • cf. Kamp’s Discourse Representation Theory – ‘John’ picks out item in (R’s MM of) story-world – ‘he’ picks out same one – ‘he’/‘John’ link inferred – ‘but’ links 2 conceptual representations • Problem: Can’t see the forest for the trees. Docsity.com Understanding a Narrative (cont’d) • Top-down approach: Global Textual Coherence – Text-structure theories: • Rumelhart’s “story grammars” • Schank’s “scripts” – Logical coherence of story world – Problem: Looks only at the forest, not at the trees Docsity.com (11 Story — > Setting + Episode = > ALLOW (Setting, Episode) (2) Setting — >(States)* = > AND (State, state, Jd (3) Episode - > Event + Reaction = > INITIATE (Event, Reaction) {a} Event - > {Episode | Change-of-state | Action | Event + Event} = > CAUSE (Event, Event,) or ALLOW (Event,, Event,) (5) Reaction — > Internal Response + Overt Response = > MOTIVATE (Interval-response, Overt Response) (6) Internal Response — > (7) Overt Response — > {Action | (Attempt)*} = > THEN (Attempt), Attempty,......) tion | Desire} (8) Attempt — > Pian + Application = > MOTIVATE (Plan, Application) (8) Application — > (Preaction)* + Action + Consequence = > ALLOW (AND(Preaction, Preaction,...), {CAUSE | INITIATE | ALLOW} (Action, Consequence}) (10) Preaction — > Subgoul + (Attempt)* = > MOTIVATE [Subgoal, THEN (Attempt, ..,..1] (11) Consequence - > {Ri FIGURE 11.4 Syntactic rules end semantic interpretation rules (from Rumelhart, 1975}. ion | Event} Story a Setting Episode ~ Resetion 4 eae of state response oo Fant Ew “ 6 a (2) (3) FIGURE 11.5 The syntactic structure of the story (from Rumelhert, 1975). Docsity com Linguistic Clues for Tracking DC (David Zubin) • Deictic operations (mental operations of the reader on the DC): – introducing – shifting – maintaining – voiding (= shift to null) • actors (WHO) • places (WHERE) • times (WHEN) Docsity.com Linguistic Clues for Tracking DC (cont’d) • Sample deictic operations on WHERE: – Hemingway: • “The door to the café opened, and two men… – came in.” WHERE = inside – went in.” WHERE = outside – entered.” WHERE = indeterminate Docsity.com Linguistic Clues for Tracking DC (cont’d) • Sample deictic operations on WHERE – Introducing/shifting (preposed adverbials): • “Kino awakened in the near dark. The stars still shone and the day had drawn only a pale wash of light….The roosters had been crowing…, and the… pigs were…turning…twigs and bits of wood to see whether anything to eat had been overlooked. Outside the brush house in the tuna clump,…birds chittered and flurried with their wings.” – Steinbeck, The Pearl – Maintaining WHERE (& shifting WHO) (deictic verbs come, go, bring, take): • “Kino squatted by the fire…and ate. When Kino had finished, Juana came back to the fire and ate.” • WHO = Kino, WHERE = location of WHO Juana enters the WHERE (come maintains the WHERE) Docsity.com Psychological Support (cont’d) • “Juana was preparing a fire. She broke little pieces of brush. Kino got up and wrapped his blanket around him. He came / went outside to watch the dawn. Kino squatted down.” • Is Juana inside the brush house? • Initial WHERE = location of WHO; indeterminate Kino’s destination = outside • came: – if female reader then WHO = Juana so WHERE = outside so Kino moved to WHERE • went: – if female reader then WHO = Juana so WHERE = inside so Kino moved from WHERE Docsity.com Communicative Disorders (Judith Felson Duchan) • Goal: – To facilitate comprehension & production of fiction in language- & learning-disabled children • Unique property of fiction: – How characters think & feel is transparent to reader (D. Cohn) • Children can manipulate mental states in fiction – 4 yrs: can understand subjective fictional experience – 6 yrs: refer to internal response of characters to events in story – Can children produce narratives using subjectivity markers? Docsity.com Communicative Disorders (cont’d) • Results: – Subject: 5-yr-old, pre-literate girl – 44 stories generated by subject from picture books – psycho-narration: 48% of stories • descriptions of thoughts of character • “she felt terrible” – internal monologues: 16% of stories • exact language of character’s thoughts • “ ‘I feel terrible’, she thought” – represented thought: 11% of stories • representation of character’s subjective experience in deictically shifted language • “She winced as she heard them crash to the platform. The lovely little mirror that she had brought for Ellen, and the gifts for the baby!” Docsity.com Computational Implementation (cont’d) • WHEN (Stuart C. Shapiro, Michael J. Almeida): – Temporal structure of narratives • WHERE (Shapiro, Albert H. Yuhan): – Reference-frame problem in narrative understanding • WHO – Belief representation (William J. Rapaport) – Recognizing subjective sentences (Janyce Wiebe) if pressed for time, can omit next 4 slides Docsity.com Computational Implementation (cont’d) • “Cassie” = name of our computational model of a reader – Cognitive Agent of the SNePS System—an Intelligent Entity :-) • SNePS nodes represent objects of Cassie’s thoughts: – “intentional” objects – individuals, properties, relations, etc. – propositions • Cassie’s “mind” grows (changes) • Cassie believes what we tell her, as if it were fictional narrative Docsity.com Computational Implementation (cont’d) • IntenSional knowledge representation: – To model a mind, a KRR system must model only intensional entities – I.e., entities that can be: • distinct, even if logically or numerically equivalent • non-existent – Argument from fine-grained representation: • intenTional entities (i.e., objects of thought) are intenSional • can have 2 objects of thought, but only 1 extensional object – morning star & evening star – President of the US, Commander-in-Chief of the US armed forces – 2+3 & 5 – Argument from displacement: • can think and talk about non-existent objects – fictional (Sherlock Holmes, Santa Claus) – impossible (mermaids, round squares) Docsity.com Computational Implementation (cont’d) • WHEN: Non-linear narrative: “John was walking to the office. He entered the office at 3:00 in the afternoon. The secretary was busy. She was typing a letter. John waited for ten minutes. He left the office. On Thursday, he returned in the morning. The secretary gave him a check. On the following Tuesday, John returned to the office. He had lost the check on the previous afternoon.” Docsity.com Computational Implementation (cont’d) • WHERE: The Reference-Frame Problem (Yuhan) “Mary, tom, and Bob went to a theater together in order to see Bob’s uncle’s show. They walked to the front of the hall. Bob sat two rows in front of Mary. Tom sat just behind her. They had a few minutes before the show would start. Mary was turned around in her seat talking with Tom. Then she saw a person who looked like Bob walking down the aisle toward her with a tall girl on his left. Recognizing Mary, he stopped in front of her to say hello. Mary glanced back and saw that Bob was still there in his seat. The person standing in front of Mary was Jim, who was Bob’s twin brother. She had met him once before. Jim and the tall girl found seats a little distance away to Mary's left. Then the lights in the hall dimmed. They saw Bob’s uncle standing behind a lectern to the left of a microphone.” Docsity.com Computational Implementation (cont’d) • WHERE: The Reference-Frame Problem (cont’d) – Input: • Mary, Tom and Bob went to a theater together in order to see Bob’s uncle’s show. – Original narrative has no explicit statement that they went in to the theater • must be inferred in order to interpret ‘front’ correctly – Output (after constructing SNePS “mental model”): • I understand that a group of individuals namely, Bob, Tom and Mary went to a theater and that they moved to a place which has a spatial relation of ideal-point to a member of the class theater. Furthermore, I infer that, presumably, the group were located at a place in a theater at a time after the time of the going and before the time of the seeing. WHEN is the time of being in the theater. WHERE is the place in the theater. WHO is the group. if pressed for time, can omit next 4 slides Docsity.com De Dicto Belief Report | @H OBJECT . 2 1 PROPER- OBJECT NAME AGENT Act OBJECT mt ma (m#) LEX LEX PROPER- NAME OBJECT OBJECT PROPERTY Mary believes that John is rich Docsity.com  [ Quasi-Indexical, De Dicto, De Se Belief Report | PROPER- OBJECT NAME OBJECT PROPERTY LEX Y @ Mary believes that she* is rich Docsity.com Computational Implementation (cont’d): AI + Literary Theory (Mary Galbraith, SDSU) • Subjectivity in narrative (Wiebe, U/Pitt) – References in narrative must often be understood w.r.t. character’s beliefs: • in subjective sentences – portraying character’s thoughts, perceptions • not in objective sentences – presenting story directly – Subjective context =def • sequence of subjective sentences portraying thoughts or perceptions of 1 character – Problem: • how to recognize subjective sentences & their character Docsity.com