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Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "32", "utterances": [ "bye bye" ] }
[ { "mode": "farewell-closing", "polarity": null, "sp-act": "echo-bye", "topic": null, "utterance": "bye bye" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "1", "utterances": [ "American Express Travel", "this is A" ] }
[ { "mode": "partial-frag", "polarity": "positive", "sp-act": "refer", "topic": null, "utterance": "American Express Travel" }, { "mode": "decl", "polarity": "positive", "sp-act": "identifySelf", "topic": null, "utterance": "this is A" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "2", "utterances": [ "hi", "i'm planning a trip to Japan at the end of uh the beginning of July" ] }
[ { "mode": "greet-opening", "polarity": null, "sp-act": "greet", "topic": null, "utterance": "hi" }, { "mode": "intent-decl", "polarity": "positive", "sp-act": "stateIntent", "topic": "country-to-month", "utterance": "i'm planning a trip to Japan at the end of uh the beginning of July" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "3", "utterances": [ "aha" ] }
[ { "mode": null, "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "aha" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "4", "utterances": [ "and i have to be there on Monday morning", "i was just wondering what time i uh you know what's the uh the latest i could leave" ] }
[ { "mode": "constrain-decl", "polarity": "positive", "sp-act": "stateConstraint", "topic": "location-time-day", "utterance": "and i have to be there on Monday morning" }, { "mode": "report-poss1-query", "polarity": "positive", "sp-act": "reqInfo", "topic": "time", "utterance": "i was just wondering what time i uh you know what's the uh the latest i could leave" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "5", "utterances": [ "ok", "and i'm speaking with" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" }, { "mode": "query", "polarity": "positive", "sp-act": "reqInfo", "topic": null, "utterance": "and i'm speaking with" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "6", "utterances": [ "B C" ] }
[ { "mode": "decl", "polarity": "positive", "sp-act": "identifySelf", "topic": null, "utterance": "B C" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "7", "utterances": [ "ok", "you you just need a schedule you said" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" }, { "mode": "report-constrain-query-disflu", "polarity": "positive", "sp-act": "reqConfirm", "topic": null, "utterance": "you you just need a schedule you said" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "8", "utterances": [ "uh yes", "i ha...", "i ca...", "i i can't travel on Saturday", "uh well", "the latest the earli... i could leave Saturday night", "probably around midnight or 11 at night" ] }
[ { "mode": null, "polarity": null, "sp-act": "confirm-acknowledge", "topic": null, "utterance": "uh yes" }, { "mode": "abandon-partial", "polarity": "positive", "sp-act": "elab-refer-abandon", "topic": null, "utterance": "i ha..." }, { "mode": "abandon-partial", "polarity": "positive", "sp-act": "refer-abandon", "topic": null, "utterance": "i ca..." }, { "mode": "poss1-disflu", "polarity": "negative", "sp-act": "expressImPossibility", "topic": "day", "utterance": "i i can't travel on Saturday" }, { "mode": null, "polarity": null, "sp-act": "init", "topic": null, "utterance": "uh well" }, { "mode": "poss1-frag", "polarity": "positive", "sp-act": "expressPossibility", "topic": "time-day", "utterance": "the latest the earli... i could leave Saturday night" }, { "mode": "opinion-probability-alternative-partial-decl", "polarity": "positive", "sp-act": "refer", "topic": "time-enum", "utterance": "probably around midnight or 11 at night" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "9", "utterances": [ "ok", "this is to Tokyo" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" }, { "mode": "query", "polarity": "positive", "sp-act": "reqInfo", "topic": "to-location_US-location_int", "utterance": "this is to Tokyo" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "10", "utterances": [ "i believe so" ] }
[ { "mode": "opinion-decl", "polarity": "positive", "sp-act": "answer-expressOpinion", "topic": null, "utterance": "i believe so" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "11", "utterances": [ "ok", "see", "i don't think they're going to have service that late", "let me tell you", "non-stop service", "the latest would be uh 1 p m arriving 3:35 p m" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" }, { "mode": null, "polarity": "positive", "sp-act": "init", "topic": null, "utterance": "see" }, { "mode": "report-opinion-decl", "polarity": "negative", "sp-act": "expressOpinion", "topic": "time", "utterance": "i don't think they're going to have service that late" }, { "mode": "decl", "polarity": "positive", "sp-act": "suggest", "topic": null, "utterance": "let me tell you" }, { "mode": "partial", "polarity": "positive", "sp-act": "refer", "topic": null, "utterance": "non-stop service" }, { "mode": "decl", "polarity": "positive", "sp-act": "state", "topic": "enum-time-arrival", "utterance": "the latest would be uh 1 p m arriving 3:35 p m" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "12", "utterances": [ "on what day" ] }
[ { "mode": "open-query", "polarity": "positive", "sp-act": "reqInfo", "topic": "day", "utterance": "on what day" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "13", "utterances": [ "on Saturday" ] }
[ { "mode": "partial-decl", "polarity": "positive", "sp-act": "answer-refer", "topic": "day", "utterance": "on Saturday" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "14", "utterances": [ "no", "i can't", "uh", "oh", "let me see", "what do you mean 1 p m", "wh... what day would i leave" ] }
[ { "mode": null, "polarity": null, "sp-act": "negate", "topic": null, "utterance": "no" }, { "mode": "poss1", "polarity": "negative", "sp-act": "expressPossibility", "topic": null, "utterance": "i can't" }, { "mode": null, "polarity": null, "sp-act": "hesitate", "topic": null, "utterance": "uh" }, { "mode": null, "polarity": null, "sp-act": "exclaim", "topic": null, "utterance": "oh" }, { "mode": null, "polarity": null, "sp-act": "hold", "topic": null, "utterance": "let me see" }, { "mode": "query-open-query", "polarity": "positive", "sp-act": "reqInfo", "topic": "enum", "utterance": "what do you mean 1 p m" }, { "mode": "open-query", "polarity": "positive", "sp-act": "reqInfo", "topic": "day", "utterance": "wh... what day would i leave" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "15", "utterances": [ "ok", "we... if you give me the days", "i can tell you the sched..." ] }
[ { "mode": "tag", "polarity": null, "sp-act": "answer-state", "topic": null, "utterance": "ok" }, { "mode": "condition-disflu", "polarity": "positive", "sp-act": "elab-stateCondition", "topic": "day", "utterance": "we... if you give me the days" }, { "mode": "poss1-interruption", "polarity": "positive", "sp-act": "expressPossibility-abandon", "topic": null, "utterance": "i can tell you the sched..." } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "16", "utterances": [ "oh", "i have a Monday morning meeting" ] }
[ { "mode": null, "polarity": null, "sp-act": "exclaim", "topic": null, "utterance": "oh" }, { "mode": "exists-decl", "polarity": "positive", "sp-act": "state", "topic": "time-day", "utterance": "i have a Monday morning meeting" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "17", "utterances": [ "ok", "you will" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" }, { "mode": "decl-interruption", "polarity": "positive", "sp-act": "state-abandon", "topic": null, "utterance": "you will" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "18", "utterances": [ "i want" ] }
[ { "mode": "intent-preference1-decl-interruption", "polarity": "positive", "sp-act": "stateIntent-abandon", "topic": null, "utterance": "i want" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "19", "utterances": [ "always arrive the following day", "so if you left on a Saturday", "you would arrive o... on a Sunday their time" ] }
[ { "mode": "decl", "polarity": "positive", "sp-act": "state", "topic": "day-arrival", "utterance": "always arrive the following day" }, { "mode": "condition-frag", "polarity": "positive", "sp-act": "stateCondition", "topic": "day", "utterance": "so if you left on a Saturday" }, { "mode": "decl", "polarity": "positive", "sp-act": "predict", "topic": "time-day-arrival", "utterance": "you would arrive o... on a Sunday their time" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "20", "utterances": [ "ok", "so", "if i", "now", "when could i", "no", "when", "so", "i... i need to arrive there you know either uh uh their time Monday early you know", "in the middle of the night would be acceptable to me anytime", "anytime", "so i can get to an office by", "i i you know i would like to arrive there certainly before 6 a m in the morning on Monday" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" }, { "mode": null, "polarity": null, "sp-act": "init", "topic": null, "utterance": "so" }, { "mode": "query-condition-frag", "polarity": "positive", "sp-act": "stateCondition-abandon", "topic": "time", "utterance": "if i" }, { "mode": null, "polarity": null, "sp-act": "init", "topic": null, "utterance": "now" }, { "mode": "open-frag", "polarity": "positive", "sp-act": "reqOpt-abandon", "topic": null, "utterance": "when could i" }, { "mode": null, "polarity": null, "sp-act": "negate", "topic": null, "utterance": "no" }, { "mode": "query-exclaim-partial-abandon", "polarity": "positive", "sp-act": "reqInfo-abandon", "topic": "time", "utterance": "when" }, { "mode": null, "polarity": null, "sp-act": "init", "topic": null, "utterance": "so" }, { "mode": "report-alternative-constrain-decl", "polarity": "positive", "sp-act": "stateConstraint", "topic": "time-location-day-arrival", "utterance": "i... i need to arrive there you know either uh uh their time Monday early you know" }, { "mode": "partial-decl", "polarity": "positive", "sp-act": "state", "topic": "time", "utterance": "in the middle of the night would be acceptable to me anytime" }, { "mode": null, "polarity": null, "sp-act": "refer", "topic": null, "utterance": "anytime" }, { "mode": "poss1", "polarity": "positive", "sp-act": "state-abandon", "topic": "time", "utterance": "so i can get to an office by" }, { "mode": "intent-decl-disflu", "polarity": "positive", "sp-act": "expressWish", "topic": "time-location-enum-day-arrival", "utterance": "i i you know i would like to arrive there certainly before 6 a m in the morning on Monday" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "21", "utterances": [ "ok then", "you'll have to leave on a Saturday", "because if you won't", "if you leave on a Sunday", "you're not gonna arrive there till in the afternoon" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "stateOpt-answer-acknowledge", "topic": null, "utterance": "ok then" }, { "mode": "constrain", "polarity": "positive", "sp-act": "elab-stateConstraint", "topic": "day", "utterance": "you'll have to leave on a Saturday" }, { "mode": "condition-reason", "polarity": "negative", "sp-act": "stateReason", "topic": "day", "utterance": "because if you won't" }, { "mode": "condition", "polarity": "positive", "sp-act": "stateCondition", "topic": "", "utterance": "if you leave on a Sunday" }, { "mode": "decl", "polarity": "negative", "sp-act": "predict", "topic": "location-time-arrival", "utterance": "you're not gonna arrive there till in the afternoon" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "22", "utterances": [ "ok" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "23", "utterances": [ "like about 3 pm on a Monday" ] }
[ { "mode": "query", "polarity": "positive", "sp-act": "reqInfo", "topic": "enum-day", "utterance": "like about 3 pm on a Monday" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "24", "utterances": [ "is is", "i... i... if i was to leave at", "oh", "i see", "a... and is there anything late on Saturday night", "cos on Saturday", "i can't leave until after 10:30 or 11 o'clock at night" ] }
[ { "mode": "disflu-abandon", "polarity": "positive", "sp-act": "answer-state-abandon", "topic": null, "utterance": "is is" }, { "mode": "condition", "polarity": "positive", "sp-act": "elab-state-abandon", "topic": null, "utterance": "i... i... if i was to leave at" }, { "mode": null, "polarity": null, "sp-act": "exclaim", "topic": null, "utterance": "oh" }, { "mode": "awareness", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "i see" }, { "mode": "exists-closed-query", "polarity": "positive", "sp-act": "reqInfo", "topic": "location-time-day", "utterance": "a... and is there anything late on Saturday night" }, { "mode": "reason-partial", "polarity": "positive", "sp-act": "referReason", "topic": "day", "utterance": "cos on Saturday" }, { "mode": "alternative-poss1-decl", "polarity": "negative", "sp-act": "state", "topic": "time-enum", "utterance": "i can't leave until after 10:30 or 11 o'clock at night" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "25", "utterances": [ "well", "the only the only way you're going", "i... it's really going to be crazy routing to do it that way", "but this is the only way to leave at night", "would have to be to fly all the way to the east coast um to fly to JFK" ] }
[ { "mode": null, "polarity": null, "sp-act": "init", "topic": null, "utterance": "well" }, { "mode": "constrain-disflu", "polarity": "positive", "sp-act": "answer-stateConstraint-abandon", "topic": null, "utterance": "the only the only way you're going" }, { "mode": "decl", "polarity": "positive", "sp-act": "elab-state", "topic": null, "utterance": "i... it's really going to be crazy routing to do it that way" }, { "mode": "constrain-decl", "polarity": "positive", "sp-act": "stateConstraint", "topic": "time", "utterance": "but this is the only way to leave at night" }, { "mode": "constrain-decl", "polarity": "positive", "sp-act": "stateConstraint", "topic": null, "utterance": "would have to be to fly all the way to the east coast um to fly to JFK" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "26", "utterances": [ "mhm" ] }
[ { "mode": "backchannel", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "mhm" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "27", "utterances": [ "and then fly from JFK to Tokyo", "so you'd be kind of going backwards", "but that's the only way that you'd be leaving at night" ] }
[ { "mode": null, "polarity": "positive", "sp-act": "state", "topic": "to-location_US-location_int", "utterance": "and then fly from JFK to Tokyo" }, { "mode": "decl", "polarity": "positive", "sp-act": "state", "topic": null, "utterance": "so you'd be kind of going backwards" }, { "mode": "constrain", "polarity": "positive", "sp-act": "stateConstraint", "topic": "time", "utterance": "but that's the only way that you'd be leaving at night" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "28", "utterances": [ "ok", "it's either that or i have to leave on Wednesday" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" }, { "mode": "alternative-abandon", "polarity": "positive", "sp-act": "state", "topic": null, "utterance": "it's either that or i have to leave on Wednesday" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "29", "utterances": [ "i see", "so" ] }
[ { "mode": "awareness", "polarity": null, "sp-act": "answer-acknowledge", "topic": null, "utterance": "i see" }, { "mode": null, "polarity": null, "sp-act": "init", "topic": null, "utterance": "so" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "30", "utterances": [ "so", "you know", "it's it's either i leave on Wednesday", "get in on Thursday", "or i leave on Saturday night", "so", "let's see which way we can do this", "it i... i... i could leave to to uh JFK on Saturday night" ] }
[ { "mode": null, "polarity": null, "sp-act": "init", "topic": null, "utterance": "so" }, { "mode": null, "polarity": null, "sp-act": "init", "topic": null, "utterance": "you know" }, { "mode": "alternative-disflu", "polarity": "positive", "sp-act": "state", "topic": "day", "utterance": "it's it's either i leave on Wednesday" }, { "mode": "frag", "polarity": "positive", "sp-act": "state", "topic": "day", "utterance": "get in on Thursday" }, { "mode": "alternative-decl", "polarity": "positive", "sp-act": "state", "topic": "day", "utterance": "or i leave on Saturday night" }, { "mode": null, "polarity": null, "sp-act": "init", "topic": null, "utterance": "so" }, { "mode": "poss1-decl", "polarity": "positive", "sp-act": "suggest", "topic": null, "utterance": "let's see which way we can do this" }, { "mode": "poss1-decl-disflu", "polarity": "positive", "sp-act": "expressPossibility", "topic": "day", "utterance": "it i... i... i could leave to to uh JFK on Saturday night" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "31", "utterances": [ "right", "let me get the uh schedule", "ok", "it would be like a 10:30 p m", "actually", "that's going to get into Newark", "let me just", "actually", "on Sunday", "it's going to go via Newark", "it's 10:30 p m", "arriving Newark at 6:35 in the morning on Sunday", "and then departing Newark at 8:25 a m", "and arriving 1:55 p m", "that's still going to arrive on Monday" ] }
[ { "mode": null, "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "right" }, { "mode": "decl", "polarity": "positive", "sp-act": "hold", "topic": null, "utterance": "let me get the uh schedule" }, { "mode": "tag", "polarity": null, "sp-act": "init", "topic": null, "utterance": "ok" }, { "mode": "opinion-decl", "polarity": "positive", "sp-act": "expressOpinion", "topic": "enum", "utterance": "it would be like a 10:30 p m" }, { "mode": "report-constrain", "polarity": null, "sp-act": "init", "topic": null, "utterance": "actually" }, { "mode": "predict-hold-frag", "polarity": "positive", "sp-act": "predict", "topic": "location_US", "utterance": "that's going to get into Newark" }, { "mode": "", "polarity": null, "sp-act": "hold", "topic": null, "utterance": "let me just" }, { "mode": "report-constrain", "polarity": null, "sp-act": "init", "topic": null, "utterance": "actually" }, { "mode": "partial-decl", "polarity": "positive", "sp-act": "refer", "topic": "day", "utterance": "on Sunday" }, { "mode": "predict", "polarity": "positive", "sp-act": "predict", "topic": "location_US", "utterance": "it's going to go via Newark" }, { "mode": "decl", "polarity": "positive", "sp-act": "state", "topic": "enum", "utterance": "it's 10:30 p m" }, { "mode": "partial-decl", "polarity": "positive", "sp-act": "state", "topic": "time-location_US-enum-day-arrival", "utterance": "arriving Newark at 6:35 in the morning on Sunday" }, { "mode": "partial-decl", "polarity": "positive", "sp-act": "state", "topic": "location_US-time-enum", "utterance": "and then departing Newark at 8:25 a m" }, { "mode": "partial-decl", "polarity": "positive", "sp-act": "state", "topic": "enum-arrival", "utterance": "and arriving 1:55 p m" }, { "mode": "decl", "polarity": "positive", "sp-act": "state", "topic": "day-arrival", "utterance": "that's still going to arrive on Monday" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "32", "utterances": [ "yeah", "i think the uh you know" ] }
[ { "mode": null, "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "yeah" }, { "mode": "opinion-interruption", "polarity": "positive", "sp-act": "expressOpinion-abandon", "topic": null, "utterance": "i think the uh you know" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "33", "utterances": [ "at 1:55" ] }
[ { "mode": "partial-decl", "polarity": "positive", "sp-act": "refer", "topic": "time", "utterance": "at 1:55" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "34", "utterances": [ "no", "that's no good", "is are", "from wh... where are there flights leaving on um Sunday morning or late Saturday night", "is there anything from Los Angeles" ] }
[ { "mode": null, "polarity": null, "sp-act": "negate", "topic": null, "utterance": "no" }, { "mode": "decl", "polarity": "negative", "sp-act": "disapprove", "topic": null, "utterance": "that's no good" }, { "mode": "abandon", "polarity": "positive", "sp-act": "abandon", "topic": null, "utterance": "is are" }, { "mode": "alternative-exists-open-query", "polarity": "positive", "sp-act": "reqInfo", "topic": "time-day-location", "utterance": "from wh... where are there flights leaving on um Sunday morning or late Saturday night" }, { "mode": "exists-closed-query", "polarity": "positive", "sp-act": "reqInfo", "topic": "location_US-location-from", "utterance": "is there anything from Los Angeles" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "35", "utterances": [ "okay", "okay", "out of San Francisco", "all the flights are afternoon", "they don't offer any morning flights to Tokyo", "and let me check Los Angeles", "ok um", "let's see", "they're still going to get you in in the afternoon on Monday", "if they leave", "there's a flight", "what airline is this", "Varig airlines at 9:50 a m", "arrives 1:30 p m on Monday" ] }
[ { "mode": null, "polarity": null, "sp-act": "answer-state", "topic": null, "utterance": "okay" }, { "mode": null, "polarity": null, "sp-act": "init", "topic": null, "utterance": "okay" }, { "mode": "frag", "polarity": "positive", "sp-act": "refer", "topic": "location_US-time", "utterance": "out of San Francisco" }, { "mode": "", "polarity": "", "sp-act": "state", "topic": "time", "utterance": "all the flights are afternoon" }, { "mode": "decl", "polarity": "negative", "sp-act": "state", "topic": "to-location_US-time-location_int", "utterance": "they don't offer any morning flights to Tokyo" }, { "mode": "hold-decl", "polarity": "positive", "sp-act": "hold", "topic": "location_US-verify", "utterance": "and let me check Los Angeles" }, { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok um" }, { "mode": null, "polarity": "positive", "sp-act": "hold", "topic": null, "utterance": "let's see" }, { "mode": "decl", "polarity": "positive", "sp-act": "state", "topic": "time-day", "utterance": "they're still going to get you in in the afternoon on Monday" }, { "mode": "condition-frag", "polarity": "positive", "sp-act": "stateCondition", "topic": null, "utterance": "if they leave" }, { "mode": "exists", "polarity": "positive", "sp-act": "state", "topic": null, "utterance": "there's a flight" }, { "mode": "open", "polarity": "positive", "sp-act": "reqInfo", "topic": null, "utterance": "what airline is this" }, { "mode": "partial-frag", "polarity": "positive", "sp-act": "refer", "topic": "time-enum-airline", "utterance": "Varig airlines at 9:50 a m" }, { "mode": "decl", "polarity": "positive", "sp-act": "enumeration", "topic": "enum-day-arrival", "utterance": "arrives 1:30 p m on Monday" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "36", "utterances": [ "no", "so", "9:50 9:50 a m arrives at what time" ] }
[ { "mode": null, "polarity": null, "sp-act": "answer-negate", "topic": null, "utterance": "no" }, { "mode": null, "polarity": null, "sp-act": "init", "topic": null, "utterance": "so" }, { "mode": "query-query-disflu", "polarity": "positive", "sp-act": "reqInfo", "topic": "time-enum-arrival", "utterance": "9:50 9:50 a m arrives at what time" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "37", "utterances": [ "1:30 p m on Monday" ] }
[ { "mode": "decl", "polarity": "positive", "sp-act": "answer-state", "topic": "enum-day", "utterance": "1:30 p m on Monday" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "38", "utterances": [ "aha", "yeah", "so i need to leave Saturday night or around midnight", "if i leave much after two in the morning on Sunday", "then i i i won't be able to make a Monday morning", "th... th... that's a direct flight so you were looking", "i guess you could either look under arrivals at Tokyo or departures on Saturday night Sunday morning" ] }
[ { "mode": null, "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "aha" }, { "mode": null, "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "yeah" }, { "mode": "report-alternative-constrain-decl", "polarity": "positive", "sp-act": "stateConstraint", "topic": "time-day", "utterance": "so i need to leave Saturday night or around midnight" }, { "mode": "condition-frag", "polarity": "positive", "sp-act": "stateCondition", "topic": "time-number-day", "utterance": "if i leave much after two in the morning on Sunday" }, { "mode": "decl-disflu", "polarity": "negative", "sp-act": "predict", "topic": "time-day", "utterance": "then i i i won't be able to make a Monday morning" }, { "mode": "report-frag", "polarity": "positive", "sp-act": "state", "topic": null, "utterance": "th... th... that's a direct flight so you were looking" }, { "mode": "opinion-poss2-alternative-frag", "polarity": "positive", "sp-act": "expressOpinion", "topic": "location_US-time-day-location_int-arrival", "utterance": "i guess you could either look under arrivals at Tokyo or departures on Saturday night Sunday morning" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "39", "utterances": [ "no", "the one i gave you is Sunday morning", "that's the third one" ] }
[ { "mode": null, "polarity": null, "sp-act": "negate", "topic": null, "utterance": "no" }, { "mode": "decl", "polarity": "positive", "sp-act": "state", "topic": "number-time-day", "utterance": "the one i gave you is Sunday morning" }, { "mode": "decl", "polarity": "positive", "sp-act": "state", "topic": "number", "utterance": "that's the third one" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "40", "utterances": [ "yeah", "9:50" ] }
[ { "mode": null, "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "yeah" }, { "mode": "decl", "polarity": "positive", "sp-act": "reqConfirm", "topic": null, "utterance": "9:50" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "41", "utterances": [ "that's correct" ] }
[ { "mode": null, "polarity": null, "sp-act": "confirm-agree", "topic": null, "utterance": "that's correct" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "42", "utterances": [ "yeah", "but that's too l..." ] }
[ { "mode": null, "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "yeah" }, { "mode": "reject-constrain-interruption", "polarity": "positive", "sp-act": "reject-abandon", "topic": null, "utterance": "but that's too l..." } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "43", "utterances": [ "that's the earliest they have", "they don't have anything else", "um", "they don't offer", "as i said they don't offer night service from the west coast to Tokyo" ] }
[ { "mode": "frag", "polarity": "positive", "sp-act": "state", "topic": "time", "utterance": "that's the earliest they have" }, { "mode": "decl", "polarity": "negative", "sp-act": "state", "topic": null, "utterance": "they don't have anything else" }, { "mode": null, "polarity": null, "sp-act": "hesitate", "topic": null, "utterance": "um" }, { "mode": "frag", "polarity": "negative", "sp-act": "state", "topic": null, "utterance": "they don't offer" }, { "mode": "report-decl", "polarity": "negative", "sp-act": "state", "topic": "to-location_US-location_int", "utterance": "as i said they don't offer night service from the west coast to Tokyo" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "44", "utterances": [ "mhm" ] }
[ { "mode": null, "polarity": null, "sp-act": "init", "topic": null, "utterance": "mhm" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "45", "utterances": [ "they only of...", "you'd have to fly all the way to the east coast", "but you're defeating the whole purpose", "because you're you're gonna still arrive Monday at 1 2 in the afternoon", "so you'd be flying 6 extra hours" ] }
[ { "mode": "abandon-constrain-abandon", "polarity": "positive", "sp-act": "abandon", "topic": null, "utterance": "they only of..." }, { "mode": "constrain", "polarity": "positive", "sp-act": "stateConstraint", "topic": null, "utterance": "you'd have to fly all the way to the east coast" }, { "mode": "constrain-frag", "polarity": "positive", "sp-act": "state", "topic": null, "utterance": "but you're defeating the whole purpose" }, { "mode": "reason-decl-disflu", "polarity": "positive", "sp-act": "stateReason", "topic": "number-time-day-arrival", "utterance": "because you're you're gonna still arrive Monday at 1 2 in the afternoon" }, { "mode": "decl", "polarity": "positive", "sp-act": "state", "topic": "enum", "utterance": "so you'd be flying 6 extra hours" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "46", "utterances": [ "no", "well", "i i i won't do that of course" ] }
[ { "mode": null, "polarity": null, "sp-act": "negate", "topic": null, "utterance": "no" }, { "mode": null, "polarity": null, "sp-act": "init", "topic": null, "utterance": "well" }, { "mode": "conviction-decl-disflu", "polarity": "negative", "sp-act": "stateIntent", "topic": null, "utterance": "i i i won't do that of course" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "47", "utterances": [ "you won...", "they don't have morning service that will get you there any earlier", "and they don't offer night service from the west coast to Tokyo" ] }
[ { "mode": "abandon", "polarity": "positive", "sp-act": "abandon", "topic": null, "utterance": "you won..." }, { "mode": "predict-decl", "polarity": "negative", "sp-act": "state", "topic": "time-location", "utterance": "they don't have morning service that will get you there any earlier" }, { "mode": "decl", "polarity": "negative", "sp-act": "state", "topic": "to-location_US-location_int", "utterance": "and they don't offer night service from the west coast to Tokyo" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "48", "utterances": [ "but the east coast does have night service" ] }
[ { "mode": "constrain-query", "polarity": "positive", "sp-act": "reqInfo", "topic": null, "utterance": "but the east coast does have night service" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "49", "utterances": [ "yeah", "but you're flying back across the US to go to Tokyo" ] }
[ { "mode": null, "polarity": null, "sp-act": "answer-acknowledge", "topic": null, "utterance": "yeah" }, { "mode": "constrain-decl", "polarity": "positive", "sp-act": "elab-state", "topic": "to-location_US-location_int", "utterance": "but you're flying back across the US to go to Tokyo" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "50", "utterances": [ "i know", "but i could do other business there" ] }
[ { "mode": "awareness", "polarity": "positive", "sp-act": "expressAwareness", "topic": null, "utterance": "i know" }, { "mode": "poss1-constrain-decl", "polarity": "positive", "sp-act": "state", "topic": "location", "utterance": "but i could do other business there" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "51", "utterances": [ "but you're still getting in at two in the mo... or two in the afternoon on Monday", "you're not saving" ] }
[ { "mode": "alternative-constrain-decl", "polarity": "positive", "sp-act": "stateConstraint", "topic": "number-time-day", "utterance": "but you're still getting in at two in the mo... or two in the afternoon on Monday" }, { "mode": null, "polarity": "negative", "sp-act": "state", "topic": null, "utterance": "you're not saving" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "52", "utterances": [ "yeah", "no", "no", "no", "i guess i don't don't need" ] }
[ { "mode": null, "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "yeah" }, { "mode": null, "polarity": null, "sp-act": "negate", "topic": null, "utterance": "no" }, { "mode": null, "polarity": null, "sp-act": "negate", "topic": null, "utterance": "no" }, { "mode": null, "polarity": null, "sp-act": "negate", "topic": null, "utterance": "no" }, { "mode": "report-opinion-constrain-decl-interruption", "polarity": "negative", "sp-act": "expressOpinion-abandon", "topic": null, "utterance": "i guess i don't don't need" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "53", "utterances": [ "yeah" ] }
[ { "mode": null, "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "yeah" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "54", "utterances": [ "there's nothing arriving in Tokyo uh uh in the", "you mean two in the afternoon i would arrive" ] }
[ { "mode": "exists-abandon", "polarity": "negative", "sp-act": "state-abandon", "topic": "location_US-location_int-arrival", "utterance": "there's nothing arriving in Tokyo uh uh in the" }, { "mode": "query-query", "polarity": "positive", "sp-act": "reqConfirm", "topic": "number-time-arrival", "utterance": "you mean two in the afternoon i would arrive" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "55", "utterances": [ "2 o'clock is the earliest", "1:55" ] }
[ { "mode": "decl", "polarity": "positive", "sp-act": "confirm-state", "topic": "time-enum", "utterance": "2 o'clock is the earliest" }, { "mode": "decl", "polarity": "positive", "sp-act": "elab-state", "topic": null, "utterance": "1:55" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "56", "utterances": [ "that's in the afternoon" ] }
[ { "mode": "decl", "polarity": "positive", "sp-act": "reqConfirm", "topic": "time", "utterance": "that's in the afternoon" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "57", "utterances": [ "right", "on Monday" ] }
[ { "mode": null, "polarity": null, "sp-act": "confirm-acknowledge", "topic": null, "utterance": "right" }, { "mode": "partial-decl", "polarity": "positive", "sp-act": "refer", "topic": "day", "utterance": "on Monday" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "58", "utterances": [ "ok", "and that's it huh" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" }, { "mode": "tag-query", "polarity": "positive", "sp-act": "reqConfirm", "topic": null, "utterance": "and that's it huh" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "59", "utterances": [ "right" ] }
[ { "mode": null, "polarity": null, "sp-act": "confirm-acknowledge", "topic": null, "utterance": "right" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "60", "utterances": [ "ok", "so in order to get in there on Friday afternoon at 2 o'clock", "i leave here" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" }, { "mode": "frag", "polarity": "positive", "sp-act": "state", "topic": "time-location-enum-day", "utterance": "so in order to get in there on Friday afternoon at 2 o'clock" }, { "mode": "query", "polarity": "positive", "sp-act": "reqInfo", "topic": "location", "utterance": "i leave here" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "61", "utterances": [ "you'd leave here Thursday" ] }
[ { "mode": "decl", "polarity": "positive", "sp-act": "answer-predict", "topic": "location-day", "utterance": "you'd leave here Thursday" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "62", "utterances": [ "Thursday is what time", "in the" ] }
[ { "mode": "query", "polarity": "positive", "sp-act": "reqInfo", "topic": "time-day", "utterance": "Thursday is what time" }, { "mode": "interruption", "polarity": "positive", "sp-act": "abandon", "topic": null, "utterance": "in the" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "63", "utterances": [ "ok", "let me get the schedules for Thursday" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "answer-acknowledge", "topic": null, "utterance": "ok" }, { "mode": "decl", "polarity": "positive", "sp-act": "hold", "topic": "day", "utterance": "let me get the schedules for Thursday" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "64", "utterances": [ "when would be the e... the earliest flight arriving on uh for Friday so" ] }
[ { "mode": "open-query", "polarity": "positive", "sp-act": "reqInfo", "topic": "time-day-arrival", "utterance": "when would be the e... the earliest flight arriving on uh for Friday so" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "65", "utterances": [ "ok", "the earliest if it's available would be the Japan Airlines", "let's see", "you want to do San Francisco", "let me check their schedules here", "i'm trying to find out which arrival is the earliest", "because non-stop", "see", "they have connections that get you in at 1:55", "but as far as non-stop service looks like 12:45 arriving 3:25 is going to be the earliest on a Thursday", "you could conceivably get in earlier", "if you wanted to uh leave San Francisco at 7 a m", "arrive Los Angeles 8:12", "and then take a Japan Airlines from Los Angeles at 10 a m", "arriving 1:20 on Thursday" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "answer-acknowledge", "topic": null, "utterance": "ok" }, { "mode": "condition-decl", "polarity": "positive", "sp-act": "elab-stateCondition", "topic": "country-availability-time", "utterance": "the earliest if it's available would be the Japan Airlines" }, { "mode": null, "polarity": null, "sp-act": "init", "topic": null, "utterance": "let's see" }, { "mode": "frag", "polarity": "positive", "sp-act": "state", "topic": "location_US", "utterance": "you want to do San Francisco" }, { "mode": "hold-decl", "polarity": "positive", "sp-act": "hold", "topic": "location-verify", "utterance": "let me check their schedules here" }, { "mode": "intent-frag", "polarity": "positive", "sp-act": "stateIntent-hold", "topic": "problem-time-arrival", "utterance": "i'm trying to find out which arrival is the earliest" }, { "mode": "reason-frag", "polarity": "positive", "sp-act": "stateReason", "topic": null, "utterance": "because non-stop" }, { "mode": null, "polarity": null, "sp-act": "init", "topic": null, "utterance": "see" }, { "mode": "decl", "polarity": "positive", "sp-act": "state", "topic": "time", "utterance": "they have connections that get you in at 1:55" }, { "mode": "constrain-frag", "polarity": "positive", "sp-act": "stateConstraint", "topic": "time-day-enum-arrival", "utterance": "but as far as non-stop service looks like 12:45 arriving 3:25 is going to be the earliest on a Thursday" }, { "mode": "poss2-suggest-decl", "polarity": "positive", "sp-act": "expressPossibility", "topic": "time", "utterance": "you could conceivably get in earlier" }, { "mode": "preference2-condition-frag", "polarity": "positive", "sp-act": "stateCondition", "topic": "location_US-time-enum", "utterance": "if you wanted to uh leave San Francisco at 7 a m" }, { "mode": "frag", "polarity": "positive", "sp-act": "state", "topic": "location_US-arrival", "utterance": "arrive Los Angeles 8:12" }, { "mode": "frag", "polarity": "positive", "sp-act": "state", "topic": "country-location_US-time-from-enum", "utterance": "and then take a Japan Airlines from Los Angeles at 10 a m" }, { "mode": "partial-decl", "polarity": "positive", "sp-act": "state", "topic": "enum-day-arrival", "utterance": "arriving 1:20 on Thursday" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "66", "utterances": [ "ok", "so that sounds like a route that i would that i would be interested in", "uh" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" }, { "mode": "decl", "polarity": "positive", "sp-act": "state", "topic": null, "utterance": "so that sounds like a route that i would that i would be interested in" }, { "mode": null, "polarity": null, "sp-act": "hesitate", "topic": null, "utterance": "uh" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "67", "utterances": [ "and book ahead because the th... the Tokyo flights sell out weeks in advance if you can" ] }
[ { "mode": "poss2-reason-condition", "polarity": "positive", "sp-act": "direct-stateReason", "topic": "location_US-location_int", "utterance": "and book ahead because the th... the Tokyo flights sell out weeks in advance if you can" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "68", "utterances": [ "ok", "can we make a reservation on that one now" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" }, { "mode": "closed-query", "polarity": "positive", "sp-act": "reqOpt", "topic": "number", "utterance": "can we make a reservation on that one now" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "69", "utterances": [ "which what is the departure date that you're referring to" ] }
[ { "mode": "open-query", "polarity": "positive", "sp-act": "reqInfo", "topic": "date", "utterance": "which what is the departure date that you're referring to" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "70", "utterances": [ "um", "i have to be there for the July 4th weekend", "it's the last week of June", "last Thursday of June" ] }
[ { "mode": null, "polarity": null, "sp-act": "hesitate", "topic": null, "utterance": "um" }, { "mode": "constrain-decl", "polarity": "positive", "sp-act": "answer-stateConstraint", "topic": "location-month", "utterance": "i have to be there for the July 4th weekend" }, { "mode": "frag", "polarity": "positive", "sp-act": "elab-state", "topic": "week-month", "utterance": "it's the last week of June" }, { "mode": "partial-decl", "polarity": "positive", "sp-act": "refer", "topic": "month-day", "utterance": "last Thursday of June" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "71", "utterances": [ "how about the 28th", "flying out on the 28th" ] }
[ { "mode": "closed-query", "polarity": "positive", "sp-act": "suggest", "topic": null, "utterance": "how about the 28th" }, { "mode": "query", "polarity": "positive", "sp-act": "reqInfo", "topic": null, "utterance": "flying out on the 28th" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "72", "utterances": [ "the 28th is a Wednesday" ] }
[ { "mode": "decl", "polarity": "positive", "sp-act": "answer-state", "topic": "day", "utterance": "the 28th is a Wednesday" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "73", "utterances": [ "yeah", "but you", "have you said you have to arrive on a Thursday" ] }
[ { "mode": null, "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "yeah" }, { "mode": "constrain-abandon", "polarity": "positive", "sp-act": "abandon", "topic": null, "utterance": "but you" }, { "mode": "report-constrain-closed-query", "polarity": "positive", "sp-act": "reqConfirm", "topic": "day-arrival", "utterance": "have you said you have to arrive on a Thursday" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "74", "utterances": [ "i have to arrive on a Friday", "i have to arrive Friday", "well", "this would arrive would bring me in Friday at 1 o'clock", "the routing that you suggested to Los Angeles" ] }
[ { "mode": "constrain-decl", "polarity": "positive", "sp-act": "correct", "topic": "day-arrival", "utterance": "i have to arrive on a Friday" }, { "mode": "constrain-decl", "polarity": "positive", "sp-act": "elab-correct", "topic": "day-arrival", "utterance": "i have to arrive Friday" }, { "mode": null, "polarity": null, "sp-act": "init", "topic": null, "utterance": "well" }, { "mode": "query", "polarity": "positive", "sp-act": "reqInfo", "topic": "time-enum-day-arrival", "utterance": "this would arrive would bring me in Friday at 1 o'clock" }, { "mode": "query", "polarity": "positive", "sp-act": "reqInfo", "topic": "to-location_US", "utterance": "the routing that you suggested to Los Angeles" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "75", "utterances": [ "ok", "let me see", "cos that was on a Wednesday", "i'm looking on a Thursday", "ok now", "is this going to be business class", "is this a business trip" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "answer-state", "topic": null, "utterance": "ok" }, { "mode": null, "polarity": null, "sp-act": "hold", "topic": null, "utterance": "let me see" }, { "mode": "reason-frag", "polarity": "positive", "sp-act": "stateReason", "topic": "day", "utterance": "cos that was on a Wednesday" }, { "mode": "decl", "polarity": "positive", "sp-act": "state", "topic": "day", "utterance": "i'm looking on a Thursday" }, { "mode": "tag", "polarity": null, "sp-act": "init", "topic": null, "utterance": "ok now" }, { "mode": "closed-query", "polarity": "positive", "sp-act": "reqInfo", "topic": null, "utterance": "is this going to be business class" }, { "mode": "closed-query", "polarity": "positive", "sp-act": "reqInfo", "topic": null, "utterance": "is this a business trip" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "76", "utterances": [ "it's a business trip", "coach business and first" ] }
[ { "mode": null, "polarity": "positive", "sp-act": "answer-state", "topic": null, "utterance": "it's a business trip" }, { "mode": "partial-query", "polarity": "positive", "sp-act": "elab", "topic": null, "utterance": "coach business and first" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "77", "utterances": [ "coach business and first", "WWW policy allows you to fly business on anything over 6 hours", "so you could fly business Los Angeles Tokyo", "ok now", "on Thursday to arrive on Friday", "ok", "let me see", "cos the schedules to Los Angeles Japan Airlines doesn't service a service on Thursday", "so it would be a Korean Airline 11 a m arriving 2:10 on Friday", "but then you... you're probably just as easy to take", "well", "it's up to you", "a non-stop out of San Francisco departs at 12 and gets in only about 30 minutes later than that", "connection through Los Angeles" ] }
[ { "mode": "partial", "polarity": "positive", "sp-act": "echo-refer", "topic": null, "utterance": "coach business and first" }, { "mode": "frag", "polarity": "positive", "sp-act": "state", "topic": "enum", "utterance": "WWW policy allows you to fly business on anything over 6 hours" }, { "mode": "poss2-suggest-decl", "polarity": "positive", "sp-act": "expressPossibility", "topic": "location_US-location_int", "utterance": "so you could fly business Los Angeles Tokyo" }, { "mode": "tag", "polarity": null, "sp-act": "init", "topic": null, "utterance": "ok now" }, { "mode": "partial", "polarity": "positive", "sp-act": "state", "topic": "day-arrival", "utterance": "on Thursday to arrive on Friday" }, { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" }, { "mode": null, "polarity": null, "sp-act": "hold", "topic": null, "utterance": "let me see" }, { "mode": "reason-frag", "polarity": "negative", "sp-act": "stateReason", "topic": "country-to-location_US-day", "utterance": "cos the schedules to Los Angeles Japan Airlines doesn't service a service on Thursday" }, { "mode": "opinion-decl", "polarity": "positive", "sp-act": "state", "topic": "enum-day-airline-arrival", "utterance": "so it would be a Korean Airline 11 a m arriving 2:10 on Friday" }, { "mode": "opinion-probability-constrain-decl", "polarity": "positive", "sp-act": "expressOpinion-abandon", "topic": null, "utterance": "but then you... you're probably just as easy to take" }, { "mode": null, "polarity": null, "sp-act": "init", "topic": null, "utterance": "well" }, { "mode": "frag", "polarity": "positive", "sp-act": "suggest", "topic": null, "utterance": "it's up to you" }, { "mode": "frag", "polarity": "positive", "sp-act": "refer", "topic": "time-location_US", "utterance": "a non-stop out of San Francisco departs at 12 and gets in only about 30 minutes later than that" }, { "mode": "decl", "polarity": "positive", "sp-act": "state", "topic": "location_US", "utterance": "connection through Los Angeles" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "78", "utterances": [ "ok" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "79", "utterances": [ "there's there's a United" ] }
[ { "mode": "exists-disflu", "polarity": "positive", "sp-act": "state", "topic": "airline", "utterance": "there's there's a United" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "80", "utterances": [ "ok", "so", "it looks like", "you know", "flying direct from here", "if i leave on Thursday", "uh", "i could do about 3 o'clock in the afternoon into Tokyo" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" }, { "mode": null, "polarity": null, "sp-act": "init", "topic": null, "utterance": "so" }, { "mode": "report-frag", "polarity": "positive", "sp-act": "abandon", "topic": null, "utterance": "it looks like" }, { "mode": null, "polarity": null, "sp-act": "phatic", "topic": null, "utterance": "you know" }, { "mode": "partial-frag", "polarity": "positive", "sp-act": "state", "topic": "location", "utterance": "flying direct from here" }, { "mode": "condition", "polarity": "positive", "sp-act": "stateCondition", "topic": "day", "utterance": "if i leave on Thursday" }, { "mode": null, "polarity": null, "sp-act": "hesitate", "topic": null, "utterance": "uh" }, { "mode": "suggest-poss1-decl", "polarity": "positive", "sp-act": "expressPossibility", "topic": "time-location_US-enum-location_int", "utterance": "i could do about 3 o'clock in the afternoon into Tokyo" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "81", "utterances": [ "right", "exactly", "there's a 12 noon arrives 2:45", "it's non-stop from San Francisco to Tokyo" ] }
[ { "mode": null, "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "right" }, { "mode": null, "polarity": null, "sp-act": "agree", "topic": null, "utterance": "exactly" }, { "mode": "exists-frag", "polarity": "positive", "sp-act": "state", "topic": "enum-arrival", "utterance": "there's a 12 noon arrives 2:45" }, { "mode": "decl", "polarity": "positive", "sp-act": "state", "topic": "location_US-to-from-location_int", "utterance": "it's non-stop from San Francisco to Tokyo" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "82", "utterances": [ "let me um just go ahead and book this United flight", "cos there aren't that many seats on that", "and what's your last name" ] }
[ { "mode": "hold-frag", "polarity": "positive", "sp-act": "hold", "topic": "airline", "utterance": "let me um just go ahead and book this United flight" }, { "mode": "reason-exists-decl", "polarity": "positive", "sp-act": "stateReason", "topic": "location", "utterance": "cos there aren't that many seats on that" }, { "mode": "open-query", "polarity": "positive", "sp-act": "reqInfo", "topic": "name", "utterance": "and what's your last name" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "83", "utterances": [ "C" ] }
[ { "mode": null, "polarity": "positive", "sp-act": "answer-state", "topic": null, "utterance": "C" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "84", "utterances": [ "and first name" ] }
[ { "mode": "query", "polarity": "positive", "sp-act": "reqInfo", "topic": "name", "utterance": "and first name" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "85", "utterances": [ "B" ] }
[ { "mode": "decl", "polarity": "positive", "sp-act": "answer-state", "topic": null, "utterance": "B" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "86", "utterances": [ "no", "i i uh i just want to make the reservation to make sure i have a spot" ] }
[ { "mode": null, "polarity": null, "sp-act": "negate", "topic": null, "utterance": "no" }, { "mode": "exists-decl-disflu", "polarity": "positive", "sp-act": "state", "topic": "verify", "utterance": "i i uh i just want to make the reservation to make sure i have a spot" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "87", "utterances": [ "ok", "and the travel advance", "we don't have yet either", "is that correct" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" }, { "mode": null, "polarity": "positive", "sp-act": "reqInfo", "topic": null, "utterance": "and the travel advance" }, { "mode": "alternative-frag", "polarity": "negative", "sp-act": "state", "topic": null, "utterance": "we don't have yet either" }, { "mode": "closed-query", "polarity": "positive", "sp-act": "reqConfirm", "topic": null, "utterance": "is that correct" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "88", "utterances": [ "no", "no", "i i might very well call you back in a few days and change it to make it earlier" ] }
[ { "mode": null, "polarity": null, "sp-act": "confirm-negate", "topic": null, "utterance": "no" }, { "mode": null, "polarity": null, "sp-act": "elab-negate", "topic": null, "utterance": "no" }, { "mode": "poss1-decl", "polarity": "positive", "sp-act": "expressPossibility", "topic": "time-day", "utterance": "i i might very well call you back in a few days and change it to make it earlier" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "89", "utterances": [ "ok", "so", "presently let me tell you what we're holding", "ok", "that's United 8 1 9 on the 29th of June", "departing San Francisco 12 noon", "and arriving Tokyo at 2:45e p m on Friday the 30th", "and that is a non-stop flight", "and what is your seating preference", "ok", "ok", "and then you're gonna call back with the rest of the itinerary on this" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" }, { "mode": null, "polarity": null, "sp-act": "init", "topic": null, "utterance": "so" }, { "mode": "decl", "polarity": "positive", "sp-act": "suggest", "topic": null, "utterance": "presently let me tell you what we're holding" }, { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" }, { "mode": "effect-frag", "polarity": "positive", "sp-act": "state", "topic": "enum-month-date-airline", "utterance": "that's United 8 1 9 on the 29th of June" }, { "mode": "partial-frag", "polarity": "positive", "sp-act": "state", "topic": "location_US-enum", "utterance": "departing San Francisco 12 noon" }, { "mode": "partial", "polarity": "positive", "sp-act": "state", "topic": "location_US-time-day-location_int-arrival", "utterance": "and arriving Tokyo at 2:45e p m on Friday the 30th" }, { "mode": "decl", "polarity": "positive", "sp-act": "state", "topic": null, "utterance": "and that is a non-stop flight" }, { "mode": "open-query", "polarity": "positive", "sp-act": "reqInfo", "topic": null, "utterance": "and what is your seating preference" }, { "mode": "tag", "polarity": null, "sp-act": "answer-acknowledge", "topic": null, "utterance": "ok" }, { "mode": "tag", "polarity": null, "sp-act": "init", "topic": null, "utterance": "ok" }, { "mode": "query", "polarity": "positive", "sp-act": "reqInfo", "topic": null, "utterance": "and then you're gonna call back with the rest of the itinerary on this" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "90", "utterances": [ "mhm" ] }
[ { "mode": "backchannel", "polarity": null, "sp-act": "answer-acknowledge", "topic": null, "utterance": "mhm" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "91", "utterances": [ "ok" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "92", "utterances": [ "ok" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "93", "utterances": [ "anything else", "ok", "thanks" ] }
[ { "mode": "query", "polarity": "positive", "sp-act": "reqInfo", "topic": null, "utterance": "anything else" }, { "mode": "tag", "polarity": null, "sp-act": "init", "topic": null, "utterance": "ok" }, { "mode": "thank", "polarity": null, "sp-act": "thank", "topic": null, "utterance": "thanks" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "94", "utterances": [ "thank you" ] }
[ { "mode": "thank", "polarity": "positive", "sp-act": "answer-state-thank", "topic": null, "utterance": "thank you" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "95", "utterances": [ "bye bye" ] }
[ { "mode": "farewell-closing", "polarity": null, "sp-act": "bye", "topic": null, "utterance": "bye bye" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "1", "utterances": [ "this is B" ] }
[ { "mode": null, "polarity": "positive", "sp-act": "identifySelf", "topic": null, "utterance": "this is B" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "2", "utterances": [ "hi", "B", "this is A from American Express" ] }
[ { "mode": "greet-opening", "polarity": null, "sp-act": "greet", "topic": null, "utterance": "hi" }, { "mode": "frag", "polarity": "positive", "sp-act": "refer", "topic": null, "utterance": "B" }, { "mode": "decl", "polarity": "positive", "sp-act": "identifySelf", "topic": "from", "utterance": "this is A from American Express" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (caller).
{ "speaker": "caller", "turn": "3", "utterances": [ "oh", "hi" ] }
[ { "mode": null, "polarity": null, "sp-act": "exclaim", "topic": null, "utterance": "oh" }, { "mode": "greet-opening", "polarity": null, "sp-act": "greet", "topic": null, "utterance": "hi" } ]
Analyze the given turn by identifying attributes such as 'sp-act', 'polarity', 'topic', and 'mode' for each utterance within the turn by the specified speaker (agent_A).
{ "speaker": "agent_A", "turn": "4", "utterances": [ "ok" ] }
[ { "mode": "tag", "polarity": null, "sp-act": "acknowledge", "topic": null, "utterance": "ok" } ]