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Sequencing and Communicative Function in Complex Dialogs Rebecca Passonneau and Owen Rambow becky, Center for Computational Learning.

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Presentation on theme: "Sequencing and Communicative Function in Complex Dialogs Rebecca Passonneau and Owen Rambow becky, Center for Computational Learning."— Presentation transcript:

1 Sequencing and Communicative Function in Complex Dialogs Rebecca Passonneau and Owen Rambow becky, rambow@ccls.columbia.edu Center for Computational Learning Systems Columbia University

2 Motivation System to analyze dialogs for understanding the outcome of the interaction o What is the outcome? o Who prevailed? o Why (status of interactants, priority of communicative action)? Can we apply common architecture to automatic analysis of interaction in email, blogs, courtrooms, phone conversations,... Question: Is Kim Ward in an inferior position to Megan Parker (Enron)?

3 Motivation (ctd) -----Original Message Number 3----- From: Parker, Megan To: Ward, Kim S (Houston) If I can get all of the information today, I can tell you this afternoon. It doesn’t take long to create the calc sheets. I understand from Janine that you or Patti can provide me with the detail that I need. If necessary, I can come pick it up. For payment, we have to forecast the money two days out. So, if I know today, I can pay on Friday. -----Original Message Number 4----- From: Ward, Kim S (Houston) To: Parker, Megan Patti is the one with the details, I’m just the deal maker and don’t have access to any of the systems.

4 Motivation (ctd) -----Original Message Number 3----- From: Parker, Megan To: Ward, Kim S (Houston) If I can get all of the information today, I can tell you this afternoon. It doesn’t take long to create the calc sheets. [Inform: Enron pay Pasadena soon, conditional on receipt of information] I understand from Janine that you or Patti can provide me with the detail that I need. If necessary, I can come pick it up. [Request for action: Kim give Megan needed information] For payment, we have to forecast the money two days out. So, if I know today, I can pay on Friday. [Inform: Friday is earliest date Enron pay Pasadena] -----Original Message Number 4----- From: Ward, Kim S (Houston) To: Parker, Megan Patti is the one with the details, I’m just the deal maker and don’t have access to any of the systems. [Reject: Kim has no info, Patti does]

5 Motivation (ctd) Conclusions: o Megan Parker supplies information which is not contradicted o Kim Ward rejects request from Megan Parker, so presumably not inferior to her o Kim and Megan searching for person to take responsibility Note: Request for action and rejection not adjacent! o Email (and other complex interactions) contain multiple, concurrent sequences (e.g., of request/response, other adjacency pairs) o Impossible to detect communicative outcome without disentangling the sequencing

6 Dialog Functional Units (DFUs) and Dialog Acts (DAs) DA = represents function (NOT form) of dialog contribution (“It is cold in here”) DFU = contiguous sequence of dialog turn which has same DA Annotation is dynamic: a first analysis may be refined when subsequent dialog contributions are processed

7 Links Between DFUs Extension of notion of “adjacency pair” o Shows links from communicative actions of one participant to the other o Can be non-adjacent o Can dynamically change the interpretation (e.g., of a previous Inform) Forward link, Backward link, Sflink Some mandatory for type of Dialog Act, some not

8 Dialog Functional Units (DFUs) Example of dynamic annotation (cf. similar example in manual) Step 1: After identifying the DFU (Inform), there is a blink, but no flink M5.2. On payment... M5.3. We are now having to forecast five days out. M5.4. If I don’t know today, I cannot pay Pasadena until next Thursday. [Inform: 5 day forecast rule] Blink2.7 Step 2: When the recipient responds to this Inform, it dynamically acquires an sflink M5.2. On payment... M5.3. We are now having to forecast five days out. M5.4. If I don’t know today, I cannot pay Pasadena until next Thursday. [Inform: 5 day forecast rule] Sflink5.2-5.4 {NEW} M6.1 thats fine [Accept: ok] Blink5.2-5.4

9 List of Dialog Acts INFORM REQUEST-INFORMATION REQUEST-ACTION COMMIT ACCEPT REJECT BACKCHANNEL PERFORM CONVENTIONAL

10 Status Developed from analysis of three very distinct types of interaction o Enron email: spontaneous; task oriented; somewhat free in types of links o Court transcript: formulaic (non-spontaneous); task oriented; very constrained in types of links (but witness can “prevail” within limits) o Switchboard: spontaneous; non-task oriented; very free in types of links Annotation Manual Annotated Text for Arabic Conversation, working on Arabic blog and English Enron

11 Plans Proposal: annotate more, in more languages, in more genres Scientific contribution: o Investigate relation of communication outcomes to types of interaction sequences across genres (blogs, emails, …) and across languages EG: how do turn-taking and other culturally specific conventions lead to same/different types of outcomes? o Similarities of DFUs/links/DAs across languages/genres o Differences of DFUs/links/DAs across languages/genres Engineering contribution: o Develop algorithms that can analyze dialogs functionally and understand interaction in different genres  Pull together analysis of outcomes across different genres  Apply similar architectures across genres/languages  Understand division between language or genre dependent vs. independent analysis of communicative outcomes

12 Enron Thread See Manual (Acrobat)

13 Arabic Conversation See Word File

14 Motivation High level o Investigate communication in different genres (blogs, emails, …) o Investigate commonalities across languages, across genres Specific phenomena we want to be able to study o Things happening in parallel, o several sequences of DAs (email message is not equivalent to turn in dialog, nor is a clause) => notion of DFU o Things happening dynamically, dialog has emergent structure Understanding dialog sequencing will permit deep understanding of dialog outcomes, even if we have deep understanding of content at the clause level; meaning emerges through the interaction in a dialog


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