Task: You are provided with a list of converations between a "USER" and "ASSISTANT". Figure out if the conversation provided as "classify_text" is authored by "USER" or "ASSISTANT". There are maximum of 7 conversations between "USER" and "ASSISTANT" in each input
Categories: Speaker Identification
Domains: Dialogue
Reasoning: Reasoning on Social Interactions

Positive examples:
input: ASSISTANT: generally speaking what type of movies do you watch , USER: I like thrillers a lot. , ASSISTANT: thrillers? for example? , USER: Zodiac's one of my favorite movies. , USER: Zodiac the movie about a serial killer from the '60s or '70s, around there. , ASSISTANT: Zodiac? oh wow ok, what do you like about that movie, classify_text: And I just think serial killers, in general, are interesting, so the movie was really good. And it was just neat to see that world. Like it went really in-depth. It was like almost 3 hours long, so you got to really feel like you were a part of that world and time period. And see what the detectives and the police did and the investigators.
output: USER
explanation: Based on last conversation in which the ASSISTANT ask's a question for which it waits for a reply from the "USER". We can classify this conversation as "USER" as it needs to respond for the given question.; input: ASSISTANT: hello. What type of movies do you like? , USER: I usually like action drama movies. , ASSISTANT: what do you like about those genres? , USER: Well, I like watching fast paced movies and I also like watching movies that have well developed story lines and characters. , ASSISTANT: okay. so do you like movies like star wars? , USER: Yeah, so I like movies like Star Wars., classify_text: what do you like about movies like that?
output: ASSISTANT
explanation: Based on last conversation the "USER" gives a response to the ASSISTANT.The classify_text then posts another question which can be classified as ASSISTANT.

Negative examples:
input: ASSISTANT: What kind of movies are you drawn to? , USER: I am drawn to romances. , ASSISTANT: Have you seen Fifty Shade of Grey? , USER: I have not. , USER: I know of it very well, but I have not seen it. , ASSISTANT: What was a movie that you last watched that surprised you?, classify_text: Maybe White House Down was surprising for me.
output: ASSISTANT
explanation: This is an example of bad output as the last coveration was based on a question asked by the "ASSISTANT" and the classify_text looks like a response to the given question.Thus the output should be "USER" instead of ASSISTANT; input: ASSISTANT: what kind of movies do you generally like? , USER: Yeah, I mostly like comedy movies. , ASSISTANT: I see. Why do you like that kind of movie? , USER: Well I like that kind of movie because you know, it'll make me laugh, and I often watch movies with my girlfriend, and I want to make sure whatever we watch, it's something we can both enjoy and and relax while watching. , ASSISTANT: That seems really nice. Can you think of a movie you really enjoyed recently? , USER: Yeah, I really enjoyed The Longest Yard with Adam Sandler., classify_text: What did you like about that movie?
output: USER
explanation: This is an example of bad output as the last coveration was an anser given by "USER" . Based on the given "classify_text" the perosn is asking another question which justifies it being an "ASSISTANT" but rather the output is "USER" which is incorrect.