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

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 , blogs, courtrooms, phone conversations,... Question: Is Kim Ward in an inferior position to Megan Parker (Enron)?

Motivation (ctd) -----Original Message Number 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 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.

Motivation (ctd) -----Original Message Number 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 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]

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 (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

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

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

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] Sflink {NEW} M6.1 thats fine [Accept: ok] Blink

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

Status Developed from analysis of three very distinct types of interaction o Enron 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

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, s, …) 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

Enron Thread See Manual (Acrobat)

Arabic Conversation See Word File

Motivation High level o Investigate communication in different genres (blogs, s, …) 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 ( 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