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Computational Models of Discourse and Dialogue 2011: Conversation in Social Media

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  1. Computational Models of Discourse and Dialogue 2011: Conversation in Social Media

  2. Persuasion in Social Media • Persuasion and argumentation in social media websites and forums

  3. NLDS Social Media Dialogue Data • Data collected in the last year in collaboration with FoxTree’s Lab &Anand’sSemLab • Convinceme.net • 4forums.org • Carm.org

  4. Using Mechanical Turk to get labels • http://pcon.soe.ucsc.edu/mturk_external/123/123.php?pageId=1597&assignmentId=ASSIGNMENT_ID_NOT_AVAILABLE&hitId=1HNBWKACQBSEV0YDIOYSBWM1C0YNIP • http://pcon.soe.ucsc.edu/mturk_external/qr/qr.php?pageId=1398&assignmentId=ASSIGNMENT_ID_NOT_AVAILABLE&hitId=1CEJFP6T9BRSEF7QNPYEV9U37T7Y6W

  5. Classic Models of Discourse and Dialogue Structure(Task Oriented Dialog, Newspaper texts) Marilyn Walker. CS245. April 1st, 2010

  6. Dialogue Processing (circa 1988) • Grosz & Sidner 1986 • Planning, Grice • Mann & Thompson 1988 • Rhetorical Relations, Text Structure • Polanyi 1984 • Linguistic Discourse Model • Hobbs 1979 • Coherence Relations

  7. Dialogue Processing (circa 1988) • Me 1989 • Starting my Ph.D. with Aravind Joshi and Ellen Prince • Science IS NOT a belief system • => Empirical Methods in Discourse

  8. Empirical/Statistical Approaches in NLP • Penn Treebank first available ~ 1990 • Plenty of data for parsing and POS • But what about language behavior above the sentence? • What about interactive language? • 1993: NSF Workshop on Centering in Naturally Occurring Discourse => Walker, Joshi & Prince 1997 • 1995: AAAI Workshop on Empirical Methods in Discourse => Walker & Moore CL special issue • 1996: NSF Workshop on Discourse & Dialogue Tagging => DAMSL markup • NOW: there is virtually no work in NLP on discourse and dialogue that is not corpus based/empirical.

  9. What is a dialogue model? • A model is an abstraction of a thing, simplified or dimensionally reduced • A good model should be simpler but capture the essence of the real thing. • A good dialogue model should be testable. It should make predictions. Its claims should be such that one should be able to prove whether or not it is correct. • A good dialogue model should lead to results that are more generalizable.

  10. Dialogue Structure • What makes a text coherent? • What are discourse structures? • Theories of discourse structures • Approaches to build discourse structures

  11. Discourse Coherence • Example: • (1) John hid Bill’s car keys. • (2) He was drunk. • (1) John hid Bill’s car keys. • (2) He likes junk food. • (1) George Bush supports big business. • (2) He’s sure to veto House Bill 1711. • Hearers try to find connections between utterances in a discourse. • The possible connections between utterances can be specified as a set of coherence relations.

  12. Coherence relations (Hobbs,1979) • Result: S0 causes S1 • John bought an Acura. His father went ballistic. • Explanation: S1 causes S0. • John hid Bill’s car keys. He was drunk. • Parallel: S0 and S1 are parallel. • John bought an Acura. Bill bought a BMW. • Elaboration: S1 is an elaboration of S0. • John bought an Acura this weekend. He purchased it for $40 thousand dollars. • …

  13. Discourse structure S1: John took a train to Bill’s car dealership. S2: He needed to buy a car. S3: The company he works for now isn’t near any public transportation. S4:He also wanted to talk to Bill about their softball leagues. ] Explanation

  14. Discourse structure S1: John took a train to Bill’s car dealership. S2: He needed to buy a car. S3: The company he works for now isn’t near any public transportation. S4:He also wanted to talk to Bill about their softball leagues. ] ] Explanation Parallel

  15. Discourse structure S1: John took a train to Bill’s car dealership. S2: He needed to buy a car. S3: The company he works for now isn’t near any public transportation. S4:He also wanted to talk to Bill about their softball leagues. ] ] Explanation Explanation ] Parallel

  16. Discourse parsing Explanation (e1) S1 (e1) Parallel (e2;e4) Explanation (e2) S4 (e4) S2(e2) S3(e3)

  17. Why compute discourse structure? • Natural language understanding • Summarization • Information retrieval • Natural language Generation • Reference resolution

  18. Theories of discourse structure • Mann and Thompson’s Rhetorical structure theory (1988) • Grosz and Sidner’s Attention, intention and structure of discourse (1986) • Discourse TAG. Penn Discourse Treebank (PDTB) • We will read a lot of papers using DTAG and PDTB so am just going to talk about these ‘classic theories’ today.

  19. Rhetorical structure theory (RST) • Mann and Thompson (1988) • One theory of discourse structure, based on identifying relations between parts of the text: • Defined 20+ rhetorical relations • Presentational relations: intentional • Subject matter relations: informational • Nucleus: central segment of text • Satellite: more peripheral segment • Relation definitions and more.

  20. Presentational (intentional) relations • Those whose intended effect is to increase some inclination in the hearer. • Relations: • Antithesis - Justify • Background - Motivation • Concession - Preparation • Enablement: - Restatement • Evidence - Summary

  21. Subject matter (information) relations • Those whose intended effect is that the hearer recognize the relation in question. • Relations • Circumstance - Otherwise • Condition - Purpose • Elaboration - Solutionhood • Evaluation - Unconditional • Interpretation - Unless • Means - Volitional cause • Non-volitional cause - Volitional result • Non-volitional result

  22. Multinuclear relations • Contrast • Joint • List • Multinuclear restatement • Sequence

  23. Some examples • Explanation: John went to the coffee shop. He was sleepy. • Elaboration: John likes coffee. He drinks it every day. • Contrast: John likes coffee. Mary hates it.

  24. Discourse structure John likes coffee They argue a lot contrast cause elaboration Mary hates coffee. He drinks it every day

  25. A relation: Evidence • (a) George Bush supports big business. • (b) He’s sure to veto House Bill 1711. • Relation Name: Evidence • Constraints on Nucl: H might not believe Nucl to a degree satisfactory to S. • Constraints on Sat: H believes Sat or will find it credible • Constraints on Nucl+Sat: H’s comprehending Sat in Sat increases H’s belief of Nucl. • Effect: H’s belief of Nucl is increased.

  26. A relation: Volitional-Cause • (a) George Bush supports big business. • (b) He’s sure to veto House Bill 1711. • Relation Name: Volitional-Cause • Constraints on Nucl: presents a volitional action • Constraints on Sat: none. • Constraints on Nucl+Sat: Sat presents a situation that could have caused the agent of the volitional action in Nucl to perform the action. • Effect: H recognizes the situation presented in Sat as a cause for the volitional action presented in Nucl.

  27. Another example S: (a) Come home by 5:00. (b) Then we can go to the hardware store before it closes. (c) That way we can finish the bookshelves tonight. (a) (a) (b) (c) motivation motivation (b) (c) condition condition

  28. A Problem with RST(Moore & Pollack, 1992) • How many rhetorical relations are there? • How can we use RST in dialogues? • How do we incorporate speaker intentions into RST? • RST does not allow for multiple relations between parts of a discourse: informational and intentional levels must coexist.

  29. Grosz & Sidner (1986)

  30. Grosz and Sidner (1986) • Three components: • Linguistic structure • Intentional structure • Attentionalstate

  31. Linguistic structure • The structure of the sequence of utterances that comprises a discourse. • Utterances form Discourse Segment (DS); and a discourse is made up of embedded DSs. • What exactly is a DS? • Any evidence that humans naturally recognize segment boundaries? • Do humans agree on segment boundaries? • How to find the boundaries automatically?

  32. Intentional structure • Speakers in a discourse may have many intentions: public or private. • Discourse purpose (DP): the intention that underlies engaging in a discourse. • Discourse segment purpose (DSP): the purpose a DS. How this segment contributes to achieving the overall DP? • Two relations between DSPs: • Dominance: if DSP1 contributes to DSP2, we say DSP2 dominates DSP1. • Satisfaction-precedence: DSP1 must be satisfied before DSP2.

  33. Attentional State • The attentional state is an abstraction of the participants’ focus of attention as their discourse unfolds. • The state is a stack of focus spaces. • A focus space (FS) is associated with a DS, and it contains DSP and objects, properties, and relations salient in the DS. • When a DS ends, its FS is popped. • When a DS starts, its FS is pushed onto the stack.

  34. An example C1: I need to travel in May. A1: And, what day in May do you want to travel? C2: I need to be there for a meeting on 15th. A2: And you are flying into what city? C3: Seattle. A3: And what time would you like to leave Pittsburgh? C4: Hmm. I don’t think there are many options for non-stop. A4: There are three non-stops today. C5: What are they? …. DS1 DS2 DS0 DS3 DS4 DS5

  35. Discourse structure with intention info • I0: C wants A to find a flight for C • I1: C wants A to know that C is traveling in May. • I2: A wants to know the departure date etc. • I3: A wants to know the destination • I4: A wants to know the departure time • I5: C wants A to find a nonstop flight DS0 DS1 DS3 DS4 DS2 DS5 C1 A1-C2 A2-C3 A3 C4-C7

  36. Problems with G&S 1986 • Assume that discourses are task-oriented • Assume there is a single, hierarchical structure shared by speaker and hearer • Do people really build such structures when they speak? Do they use them in interpreting what others say?

  37. Walker 1996: Limited Attention & Discourse Structure

  38. LIMITED ATTENTION CONSTRAINTWalker 1993, 1996 • ellipsis interpretation • pronominal anaphora interpretation • inference of discourse relations between utterances A and B • B MOTIVATES A • B is EVIDENCE for A

  39. How is attention modeled ? • Linear Recency • Hierarchical Recency

  40. Centering • Centering is formulated as a theory that relates focus of attention, choice of referring expression, and perceived coherence of utterances, within a discourse segment [Grosz et al., 1995]. • Brennan, Walker & Pollard 1987: Centering theory of Anaphora Resolution

  41. What about Processing & Centering?

  42. Informationally Redundant Utterances

  43. Centers cross segments • Centers continued over discourse segment boundaries with pronominal referring expressions whose form is identical to those that occur within a discourse segment. • (29) and he's going to take a pear or two, and then.. go on his way • (30) um but the little boy comes, • (31) and uh he doesn't want just a pear, • (32) he wants a whole basket. • (33) So he puts the bicycle down, • (34) and he.. • [Pear Stories, Chafe, 1980; Passonneau, 1995]: • => discourse segment boundary between (32) and (33). [Passonneau, 1995, Passonneau & Litman 1997] • [Walker et al., 1998], (33) realizes a CONTINUE transition, indicating that utterance (33) is highly coherent in the context of utterance (32).

  44. Why is centering only within Segment? • It is not plausible that a different process than centering would be required to explain the relationship between utterances (32) and (33), simply because these utterances span a discourse segment boundary. • Centering is a theory that relates focus of attention, choice of referring expression, and perceived coherence of utterances, within a discourse segment [Joshi & Weinstein 1983, Grosz, Joshi & Weinstein, 1995],

  45. Cache Model (Human Working Memory)

  46. Building discourse structure

  47. Tasks • Identify units, e.g. discourse segment boundaries • Determine relations between segments • Determine intentions of the segments • Determine the attentional state • Methods: • Inference-based approach: symbolic • Cue-based approach: statistical

  48. Inference-based approach • Ex: John hid Bill’s car keys. He was drunk. • X is drunk  people do not want X to drive • People don’t want X to drive  people hide X’s car key. • Abduction: •  AI-complete: Require and utilize world knowledge.

  49. Cue-based approach • Attentional state: • Attentional changes: • (push) now, next, but, …. • (pop) anyway, in any case, now back to, ok, fine,... • True interruption: excuse me, I must interrupt • Flashback: oops, I forgot • Intention: • Satisfaction-precedes: first, second, furthermore, …. • Dominance: for example, first, second, ….

  50. Cues (cont) • Linguistic structure • Elaboration: for example, … • Concession: although • Condition: if • Sequence: and, first, second. • Contrast: and, … • …