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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 (agent_A). | {
"speaker": "agent_A",
"turn": "1",
"utterances": [
"American Express Travel",
"this is A"
]
} | [
{
"mode": "partial",
"polarity": "positive",
"sp-act": "refer",
"topic": null,
"utterance": "American Express Travel"
},
{
"mode": null,
"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": [
"uh",
"A",
"this is uh B",
"i need to make some reservations",
"i need to make uh reservations",
"and all i know at this uh time is my flight out uh departing on Monday",
"what do you need first"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "hesitate",
"topic": null,
"utterance": "uh"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "refer",
"topic": null,
"utterance": "A"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "identifySelf",
"topic": null,
"utterance": "this is uh B"
},
{
"mode": "report-constrain-decl",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "i need to make some reservations"
},
{
"mode": "report-constrain",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "i need to make uh reservations"
},
{
"mode": "awareness-decl",
"polarity": "positive",
"sp-act": "expressAwareness",
"topic": "time-day",
"utterance": "and all i know at this uh time is my flight out uh departing on Monday"
},
{
"mode": "constrain-open-query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": null,
"utterance": "what do you need 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": "3",
"utterances": [
"ok",
"let me let me pull up your profile first",
"ok",
"and the date that we know we're booking is on what day"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "answer-acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "decl-disflu",
"polarity": "positive",
"sp-act": "hold",
"topic": null,
"utterance": "let me let me pull up your profile first"
},
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": "date-day",
"utterance": "and the date that we know we're booking is 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 (caller). | {
"speaker": "caller",
"turn": "4",
"utterances": [
"um",
"it's Monday the 20th"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "hesitate",
"topic": null,
"utterance": "um"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "answer-state",
"topic": "day",
"utterance": "it's Monday the 20th"
}
] |
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": [
"and that's flying to what city"
]
} | [
{
"mode": "query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": null,
"utterance": "and that's flying to what city"
}
] |
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": [
"uh",
"to Newark",
"United flight number 12",
"and i'd like first class if it's available",
"i'm gonna use an upgrade coupon which is coming Federal Express tomorrow or Wednesday",
"that's the 19th",
"i'm sorry"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "hesitate",
"topic": null,
"utterance": "uh"
},
{
"mode": "partial",
"polarity": "positive",
"sp-act": "answer-refer",
"topic": "to-location_US",
"utterance": "to Newark"
},
{
"mode": "partial",
"polarity": "positive",
"sp-act": "elab-refer",
"topic": "number-airline",
"utterance": "United flight number 12"
},
{
"mode": "condition-decl",
"polarity": "positive",
"sp-act": "state",
"topic": "availability",
"utterance": "and i'd like first class if it's available"
},
{
"mode": "intent-alternative-decl",
"polarity": "positive",
"sp-act": "stateIntent",
"topic": "day",
"utterance": "i'm gonna use an upgrade coupon which is coming Federal Express tomorrow or Wednesday"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "that's the 19th"
},
{
"mode": "regret-decl",
"polarity": "positive",
"sp-act": "apologise",
"topic": null,
"utterance": "i'm sorry"
}
] |
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": [
"now",
"that's on the 19th"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "now"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "reqConfirm",
"topic": null,
"utterance": "that's on the 19th"
}
] |
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": [
"yeah",
"i'm sorry",
"i thought Monday was the 20th"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "yeah"
},
{
"mode": "regret-decl",
"polarity": "positive",
"sp-act": "apologise",
"topic": null,
"utterance": "i'm sorry"
},
{
"mode": "report-opinion-decl",
"polarity": "positive",
"sp-act": "state",
"topic": "day",
"utterance": "i thought Monday was the 20th"
}
] |
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",
"do know wha... which award um"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "reqInfo",
"topic": null,
"utterance": "do know wha... which award um"
}
] |
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": [
"well",
"it's uh a regular um mileage plus upgrade where you use the miles you've accumulated",
"so it's good for booking first class",
"all i have to do is give you the coupon",
"it's it's uh the number one priority type of uh"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "well"
},
{
"mode": "report-decl",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "it's uh a regular um mileage plus upgrade where you use the miles you've accumulated"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "so it's good for booking first class"
},
{
"mode": "constrain",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "all i have to do is give you the coupon"
},
{
"mode": "disflu",
"polarity": "positive",
"sp-act": "state",
"topic": "number",
"utterance": "it's it's uh the number one priority type of 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": "11",
"utterances": [
"ok",
"and is it for one way or round trip or per segment"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "closed",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": "number",
"utterance": "and is it for one way or round trip or per segment"
}
] |
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": [
"it's round trip",
"but if i only use it one way",
"it doesn't matter",
"it's a ro... round trip",
"i mean",
"i have to forfeit the rest of it"
]
} | [
{
"mode": "decl",
"polarity": "positive",
"sp-act": "answer-state",
"topic": null,
"utterance": "it's round trip"
},
{
"mode": "constrain-condition",
"polarity": "positive",
"sp-act": "elab-stateCondition",
"topic": "number",
"utterance": "but if i only use it one way"
},
{
"mode": null,
"polarity": "negative",
"sp-act": "state",
"topic": null,
"utterance": "it doesn't matter"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "it's a ro... round trip"
},
{
"mode": null,
"polarity": null,
"sp-act": "phatic",
"topic": null,
"utterance": "i mean"
},
{
"mode": "constrain-decl",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "i have to forfeit the rest of it"
}
] |
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": [
"ok",
"that's uh United flight 12 on the 12th of June"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "effect-query",
"polarity": "positive",
"sp-act": "reqConfirm",
"topic": "month-date-enum-airline",
"utterance": "that's uh United flight 12 on the 12th 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 (caller). | {
"speaker": "caller",
"turn": "14",
"utterances": [
"yeah"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "confirm-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 (agent_A). | {
"speaker": "agent_A",
"turn": "15",
"utterances": [
"oh",
"wait",
"wait",
"wait",
"wait",
"you said the 19th"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "exclaim",
"topic": null,
"utterance": "oh"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "hold",
"topic": null,
"utterance": "wait"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "hold",
"topic": null,
"utterance": "wait"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "hold",
"topic": null,
"utterance": "wait"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "hold",
"topic": null,
"utterance": "wait"
},
{
"mode": "report-query",
"polarity": "positive",
"sp-act": "reqConfirm",
"topic": null,
"utterance": "you said the 19th"
}
] |
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": [
"19th",
"i'm sorry"
]
} | [
{
"mode": null,
"polarity": "positive",
"sp-act": "echo-confirm",
"topic": null,
"utterance": "19th"
},
{
"mode": "regret",
"polarity": "positive",
"sp-act": "apologise",
"topic": null,
"utterance": "i'm sorry"
}
] |
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": [
"i put 20th",
"that's all right"
]
} | [
{
"mode": null,
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "i put 20th"
},
{
"mode": "reassurance-tag-decl",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "that's all 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 (agent_A). | {
"speaker": "agent_A",
"turn": "18",
"utterances": [
"ok",
"let me change that"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "suggest",
"topic": null,
"utterance": "let me change that"
}
] |
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": "19",
"utterances": [
"Monday isn't the best time"
]
} | [
{
"mode": "decl",
"polarity": "negative",
"sp-act": "state",
"topic": "time-day",
"utterance": "Monday isn't the best 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": "20",
"utterances": [
"no",
"it isn't",
"ok",
"so",
"that's United flight 12 on the 19th of June"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "negate",
"topic": null,
"utterance": "no"
},
{
"mode": "decl",
"polarity": "negative",
"sp-act": "agree",
"topic": null,
"utterance": "it isn't"
},
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "so"
},
{
"mode": "effect-query",
"polarity": "positive",
"sp-act": "reqConfirm",
"topic": "month-date-enum-airline",
"utterance": "that's United flight 12 on the 19th 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 (caller). | {
"speaker": "caller",
"turn": "21",
"utterances": [
"yeah"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "confirm-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 (agent_A). | {
"speaker": "agent_A",
"turn": "22",
"utterances": [
"departing San Francisco at 8:20 a m"
]
} | [
{
"mode": "partial-query",
"polarity": "positive",
"sp-act": "reqConfirm",
"topic": "location_US-time-enum",
"utterance": "departing San Francisco at 8:20 a 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": "23",
"utterances": [
"yeah"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "confirm-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 (agent_A). | {
"speaker": "agent_A",
"turn": "24",
"utterances": [
"arriving Newark at 4:43 p m"
]
} | [
{
"mode": "partial-query",
"polarity": "positive",
"sp-act": "reqConfirm",
"topic": "location_US-time-enum-arrival",
"utterance": "arriving Newark at 4:43 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": "25",
"utterances": [
"right",
"so uh",
"now",
"i'm not i'm still making uh reservations or er appointments for the rest of the week",
"so i'll have to get back to you on the return"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "confirm-acknowledge",
"topic": null,
"utterance": "right"
},
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "so uh"
},
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "now"
},
{
"mode": "alternative-frag",
"polarity": "negative",
"sp-act": "state",
"topic": null,
"utterance": "i'm not i'm still making uh reservations or er appointments for the rest of the week"
},
{
"mode": "intent-constrain-decl",
"polarity": "positive",
"sp-act": "stateIntent",
"topic": null,
"utterance": "so i'll have to get back to you on the return"
}
] |
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": "26",
"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": "27",
"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": "28",
"utterances": [
"that's fine",
"ok",
"thanks",
"A"
]
} | [
{
"mode": "reassurance",
"polarity": null,
"sp-act": "approve",
"topic": null,
"utterance": "that's fine"
},
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "thank",
"polarity": null,
"sp-act": "thank",
"topic": null,
"utterance": "thanks"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "refer",
"topic": null,
"utterance": "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": "29",
"utterances": [
"thank you"
]
} | [
{
"mode": "thank",
"polarity": "positive",
"sp-act": "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": "30",
"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": "31",
"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 (agent_A). | {
"speaker": "agent_A",
"turn": "32",
"utterances": [
"bye"
]
} | [
{
"mode": "farewell-closing",
"polarity": null,
"sp-act": "echo-bye",
"topic": null,
"utterance": "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": [
"this is A at American Express",
"may i help you"
]
} | [
{
"mode": "frag",
"polarity": "positive",
"sp-act": "identifySelf",
"topic": "time",
"utterance": "this is A at American Express"
},
{
"mode": "closed-query",
"polarity": "positive",
"sp-act": "offer",
"topic": null,
"utterance": "may i help 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 (caller). | {
"speaker": "caller",
"turn": "2",
"utterances": [
"A",
"this is B"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "refer",
"topic": null,
"utterance": "A"
},
{
"mode": "decl",
"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": "3",
"utterances": [
"ok",
"what can i help you with",
"B"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "open-query",
"polarity": "positive",
"sp-act": "reqDirect",
"topic": null,
"utterance": "what can i help you with"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "refer",
"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": "4",
"utterances": [
"ok",
"my the traveller is C"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "ok"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "my the traveller is 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": "5",
"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 (caller). | {
"speaker": "caller",
"turn": "6",
"utterances": [
"first name is CC"
]
} | [
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": "name",
"utterance": "first name is CC"
}
] |
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",
"what does he need to do"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "constrain-open-query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": null,
"utterance": "what does he need to do"
}
] |
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": [
"ok",
"it's for eh the outbound would be on June 17th"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "answer-state",
"topic": "month",
"utterance": "it's for eh the outbound would be on June 17th"
}
] |
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": [
"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": "10",
"utterances": [
"and it's on US Air flight 2 7 8 2",
"and i believe it's departing at 12:25 p m"
]
} | [
{
"mode": "frag",
"polarity": "positive",
"sp-act": "state",
"topic": "enum",
"utterance": "and it's on US Air flight 2 7 8 2"
},
{
"mode": "opinion-decl",
"polarity": "positive",
"sp-act": "expressOpinion",
"topic": "time-enum",
"utterance": "and i believe it's departing at 12:25 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 (agent_A). | {
"speaker": "agent_A",
"turn": "11",
"utterances": [
"going where"
]
} | [
{
"mode": "query-open-query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": null,
"utterance": "going where"
}
] |
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": [
"Orange County"
]
} | [
{
"mode": "partial-decl",
"polarity": "positive",
"sp-act": "answer-refer",
"topic": "location_US",
"utterance": "Orange County"
}
] |
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": [
"2:25 p m"
]
} | [
{
"mode": "query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": "enum",
"utterance": "2:25 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": "14",
"utterances": [
"yes uh",
"12:25",
"sorry"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "answer-acknowledge",
"topic": null,
"utterance": "yes uh"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "correct",
"topic": null,
"utterance": "12:25"
},
{
"mode": "regret",
"polarity": null,
"sp-act": "pardon",
"topic": null,
"utterance": "sorry"
}
] |
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",
"US Air flight 2 7 8 2"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "query",
"polarity": "positive",
"sp-act": "reqConfirm",
"topic": "enum",
"utterance": "US Air flight 2 7 8 2"
}
] |
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": [
"mhm",
"yeah"
]
} | [
{
"mode": "backchannel",
"polarity": null,
"sp-act": "confirm-acknowledge",
"topic": null,
"utterance": "mhm"
},
{
"mode": null,
"polarity": null,
"sp-act": "elab-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 (agent_A). | {
"speaker": "agent_A",
"turn": "17",
"utterances": [
"ok",
"got that"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "got that"
}
] |
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": [
"that",
"right",
"ok",
"now",
"this traveller is making",
"uh",
"this is something out of the ordinary now",
"it says reservations for CC and his wife and"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "echo-refer",
"topic": null,
"utterance": "that"
},
{
"mode": "tag-query",
"polarity": "positive",
"sp-act": "acknowledge",
"topic": null,
"utterance": "right"
},
{
"mode": "tag",
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "ok"
},
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "now"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "abandon",
"topic": null,
"utterance": "this traveller is making"
},
{
"mode": null,
"polarity": null,
"sp-act": "hesitate",
"topic": null,
"utterance": "uh"
},
{
"mode": "frag",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "this is something out of the ordinary now"
},
{
"mode": "report-interruption",
"polarity": "positive",
"sp-act": "state-abandon",
"topic": null,
"utterance": "it says reservations for CC and his wife and"
}
] |
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": [
"yeah",
"let me make C's reservation",
"and then i'll have to call US Air to find out if if we're allowed to make her reservations",
"sometimes you have to make it directly with the airline"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "yeah"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "suggest",
"topic": null,
"utterance": "let me make C's reservation"
},
{
"mode": "intent-condition-constrain-decl",
"polarity": "positive",
"sp-act": "stateIntent",
"topic": null,
"utterance": "and then i'll have to call US Air to find out if if we're allowed to make her reservations"
},
{
"mode": "constrain-decl",
"polarity": "positive",
"sp-act": "stateConstraint",
"topic": null,
"utterance": "sometimes you have to make it directly with the airline"
}
] |
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": [
"oh"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "exclaim",
"topic": null,
"utterance": "oh"
}
] |
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": [
"and if we can make it",
"i'll go ahead and do it"
]
} | [
{
"mode": "poss1-condition",
"polarity": "positive",
"sp-act": "stateCondition",
"topic": null,
"utterance": "and if we can make it"
},
{
"mode": "intent-decl",
"polarity": "positive",
"sp-act": "stateIntent",
"topic": null,
"utterance": "i'll go ahead and do it"
}
] |
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": [
"oh",
"ok"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "exclaim",
"topic": null,
"utterance": "oh"
},
{
"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": [
"ok",
"otherwise you'll have to call US Air"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "ok"
},
{
"mode": "constrain-decl",
"polarity": "positive",
"sp-act": "stateConstraint",
"topic": null,
"utterance": "otherwise you'll have to call US Air"
}
] |
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": [
"oh",
"i see",
"all right",
"now",
"coming back on June 20th"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "exclaim",
"topic": null,
"utterance": "oh"
},
{
"mode": "awareness",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "i see"
},
{
"mode": "tag",
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "all right"
},
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "now"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": "month",
"utterance": "coming back on June 20th"
}
] |
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": [
"leaving at what time"
]
} | [
{
"mode": "query-open-query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": "time",
"utterance": "leaving 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 (caller). | {
"speaker": "caller",
"turn": "26",
"utterances": [
"uh let's see",
"5:10 p m out of Burbank",
"and this is on US Air 2 5 1 1",
"and again this return flight will be for CC and his wife"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "hold",
"topic": null,
"utterance": "uh let's see"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "answer-refer",
"topic": "location_US-enum",
"utterance": "5:10 p m out of Burbank"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "elab-state",
"topic": "enum",
"utterance": "and this is on US Air 2 5 1 1"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "reqConfirm",
"topic": null,
"utterance": "and again this return flight will be for CC and his wife"
}
] |
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": [
"right",
"n... yeah",
"i know"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "confirm-acknowledge",
"topic": null,
"utterance": "right"
},
{
"mode": null,
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "n... yeah"
},
{
"mode": "awareness-decl",
"polarity": "positive",
"sp-act": "expressAwareness",
"topic": null,
"utterance": "i 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 (caller). | {
"speaker": "caller",
"turn": "28",
"utterances": [
"you'll have to check that one too"
]
} | [
{
"mode": "constrain-decl",
"polarity": "positive",
"sp-act": "direct-state",
"topic": "number-verify",
"utterance": "you'll have to check that one too"
}
] |
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": [
"no",
"i'll check the whole thing",
"yeah"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "negate",
"topic": null,
"utterance": "no"
},
{
"mode": "intent-decl",
"polarity": "positive",
"sp-act": "stateIntent-hold",
"topic": "verify",
"utterance": "i'll check the whole thing"
},
{
"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": "30",
"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": "31",
"utterances": [
"what's his wife's name"
]
} | [
{
"mode": "open-query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": "name",
"utterance": "what's his wife's 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": "32",
"utterances": [
"eh",
"huh"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "hesitate",
"topic": null,
"utterance": "eh"
},
{
"mode": "tag",
"polarity": "positive",
"sp-act": "pardon",
"topic": null,
"utterance": "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": "33",
"utterances": [
"yeah",
"we have enough advance purchase time that i can get a non-refundable fare on the return",
"would bring that portion down to 29 dollars one way",
"but i'd have to t... issue the tickets today"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "yeah"
},
{
"mode": "poss1-decl",
"polarity": "positive",
"sp-act": "expressPossibility",
"topic": "time",
"utterance": "we have enough advance purchase time that i can get a non-refundable fare on the return"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": "number-enum",
"utterance": "would bring that portion down to 29 dollars one way"
},
{
"mode": "constrain-decl",
"polarity": "positive",
"sp-act": "stateConstraint",
"topic": "day",
"utterance": "but i'd have to t... issue the tickets today"
}
] |
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",
"give them the non-restricted air fare",
"i think it's 1 9 0 8"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "negate",
"topic": null,
"utterance": "no"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "direct",
"topic": null,
"utterance": "give them the non-restricted air fare"
},
{
"mode": "opinion-decl",
"polarity": "positive",
"sp-act": "expressOpinion",
"topic": "enum",
"utterance": "i think it's 1 9 0 8"
}
] |
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": [
"non-restrictive air fare",
"1 9 0 8",
"right",
"ok",
"sure"
]
} | [
{
"mode": null,
"polarity": "positive",
"sp-act": "echo-refer",
"topic": null,
"utterance": "non-restrictive air fare"
},
{
"mode": "tag-decl",
"polarity": "positive",
"sp-act": "echo-refer",
"topic": "enum",
"utterance": "1 9 0 8"
},
{
"mode": null,
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "right"
},
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": null,
"polarity": null,
"sp-act": "agree",
"topic": null,
"utterance": "sure"
}
] |
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": "37",
"utterances": [
"bye"
]
} | [
{
"mode": "farewell-closing",
"polarity": null,
"sp-act": "bye",
"topic": null,
"utterance": "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": "38",
"utterances": [
"bye bye",
"B"
]
} | [
{
"mode": "farewell-closing",
"polarity": null,
"sp-act": "echo-bye",
"topic": null,
"utterance": "bye bye"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "refer",
"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 (agent_A). | {
"speaker": "agent_A",
"turn": "1",
"utterances": [
"hi",
"this is A at American Express",
"may i help you"
]
} | [
{
"mode": "greet-opening",
"polarity": null,
"sp-act": "greet",
"topic": null,
"utterance": "hi"
},
{
"mode": "frag",
"polarity": "positive",
"sp-act": "identifySelf",
"topic": "time",
"utterance": "this is A at American Express"
},
{
"mode": "closed-query",
"polarity": "positive",
"sp-act": "offer",
"topic": null,
"utterance": "may i help 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 (caller). | {
"speaker": "caller",
"turn": "2",
"utterances": [
"hi",
"A",
"this is B",
"Physical Sciences Business Office at uh WWW"
]
} | [
{
"mode": "greet-opening",
"polarity": null,
"sp-act": "greet",
"topic": null,
"utterance": "hi"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "refer",
"topic": null,
"utterance": "A"
},
{
"mode": "frag",
"polarity": "positive",
"sp-act": "identifySelf",
"topic": null,
"utterance": "this is B"
},
{
"mode": "partial-decl",
"polarity": "positive",
"sp-act": "refer",
"topic": "time",
"utterance": "Physical Sciences Business Office at uh WWW"
}
] |
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": [
"yeah",
"and uh what can i help you with"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "yeah"
},
{
"mode": "open-query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": null,
"utterance": "and uh what can i help you 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": "4",
"utterances": [
"uh",
"i need to know uh business class round trip uh fare for uh San Francisco to uh Baron Switzerland"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "hesitate",
"topic": null,
"utterance": "uh"
},
{
"mode": "report-constrain-decl",
"polarity": "positive",
"sp-act": "answer-state",
"topic": "country-to-location_US-location_int",
"utterance": "i need to know uh business class round trip uh fare for uh San Francisco to uh Baron Switzerland"
}
] |
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": [
"sure",
"one second",
"is this for a proposal"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "sure"
},
{
"mode": null,
"polarity": null,
"sp-act": "hold",
"topic": null,
"utterance": "one second"
},
{
"mode": "closed-query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": null,
"utterance": "is this for a proposal"
}
] |
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": [
"right"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "answer-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 (agent_A). | {
"speaker": "agent_A",
"turn": "7",
"utterances": [
"i'm checking a couple different carriers just to compare them before i give you the fare on this"
]
} | [
{
"mode": "intent-decl",
"polarity": "positive",
"sp-act": "stateIntent-hold",
"topic": "verify-time",
"utterance": "i'm checking a couple different carriers just to compare them before i give you the fare 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": "8",
"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": "9",
"utterances": [
"i seem to have a very slow computer here"
]
} | [
{
"mode": "awareness-decl",
"polarity": "positive",
"sp-act": "expressAwareness-hold",
"topic": "location",
"utterance": "i seem to have a very slow computer 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 (caller). | {
"speaker": "caller",
"turn": "10",
"utterances": [
"ok",
"that's all right"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "reassurance-tag-decl",
"polarity": "positive",
"sp-act": "agree",
"topic": null,
"utterance": "that's all 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 (agent_A). | {
"speaker": "agent_A",
"turn": "11",
"utterances": [
"well",
"i have one fare",
"let me give you that",
"and i'm just trying to see if i can verify it on another carrier"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "well"
},
{
"mode": "exists-decl",
"polarity": "positive",
"sp-act": "state",
"topic": "number",
"utterance": "i have one fare"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "offer",
"topic": null,
"utterance": "let me give you that"
},
{
"mode": "intent-report-hold-poss1-condition-decl",
"polarity": "positive",
"sp-act": "stateIntent-hold",
"topic": "problem-verify",
"utterance": "and i'm just trying to see if i can verify it on another carrier"
}
] |
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": [
"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": "13",
"utterances": [
"uh",
"one way fare would be 1567"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "hesitate",
"topic": null,
"utterance": "uh"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": "number",
"utterance": "one way fare would be 1567"
}
] |
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": [
"w... round trip"
]
} | [
{
"mode": "partial-query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": null,
"utterance": "w... round 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 (agent_A). | {
"speaker": "agent_A",
"turn": "15",
"utterances": [
"the round trip would be that times 2 plus 13 for taxes"
]
} | [
{
"mode": "decl",
"polarity": "positive",
"sp-act": "answer-state",
"topic": "enum",
"utterance": "the round trip would be that times 2 plus 13 for taxes"
}
] |
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": [
"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": "17",
"utterances": [
"uh",
"it looks like approximately right",
"uh",
"using TWA instead of American",
"i get 1589",
"a little bit higher"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "hesitate",
"topic": null,
"utterance": "uh"
},
{
"mode": "report-tag-frag",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "it looks like approximately right"
},
{
"mode": null,
"polarity": null,
"sp-act": "hesitate",
"topic": null,
"utterance": "uh"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "using TWA instead of American"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "i get 1589"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "a little bit higher"
}
] |
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": [
"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": "19",
"utterances": [
"so",
"it's it's in that ballpark"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "so"
},
{
"mode": "disflu",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "it's it's in that ballpark"
}
] |
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",
"15 57 times 2 plus 13"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "refer",
"topic": "enum",
"utterance": "15 57 times 2 plus 13"
}
] |
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": [
"there isn't any one carrier that flies all the way in there",
"you need to connect somewhere like from TWA to Air France or Pan Am to Air France or something to get in to Baron"
]
} | [
{
"mode": "exists-decl",
"polarity": "negative",
"sp-act": "state",
"topic": "number-location",
"utterance": "there isn't any one carrier that flies all the way in there"
},
{
"mode": "alternative-constrain-decl",
"polarity": "positive",
"sp-act": "stateConstraint",
"topic": "to-airline-country-location_int",
"utterance": "you need to connect somewhere like from TWA to Air France or Pan Am to Air France or something to get in to Baron"
}
] |
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": [
"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 (agent_A). | {
"speaker": "agent_A",
"turn": "23",
"utterances": [
"and also you can't get business class all the way through",
"but they fare it business class all the way"
]
} | [
{
"mode": "poss2-frag",
"polarity": "negative",
"sp-act": "expressImPossibility",
"topic": null,
"utterance": "and also you can't get business class all the way through"
},
{
"mode": "constrain-decl",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "but they fare it business class all the way"
}
] |
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": [
"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": "25",
"utterances": [
"you you you would get business class from the US to your European gateway city",
"and then for the little hop to Baron",
"you would probably be in Coach"
]
} | [
{
"mode": "decl-disflu",
"polarity": "positive",
"sp-act": "state",
"topic": "location_int",
"utterance": "you you you would get business class from the US to your European gateway city"
},
{
"mode": "partial",
"polarity": "positive",
"sp-act": "refer",
"topic": "to-location_int",
"utterance": "and then for the little hop to Baron"
},
{
"mode": "opinion-probability-decl",
"polarity": "positive",
"sp-act": "expressOpinion",
"topic": null,
"utterance": "you would probably be in Coach"
}
] |
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": [
"yeah",
"ok"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "yeah"
},
{
"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": "27",
"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": "28",
"utterances": [
"that helps"
]
} | [
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "that helps"
}
] |
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": [
"ok",
"great"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": null,
"polarity": null,
"sp-act": "approve",
"topic": null,
"utterance": "great"
}
] |
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": [
"thanks a lot"
]
} | [
{
"mode": "thank",
"polarity": null,
"sp-act": "thank",
"topic": null,
"utterance": "thanks a lot"
}
] |
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": [
"you're welcome",
"bye bye"
]
} | [
{
"mode": null,
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "you're welcome"
},
{
"mode": "farewell-closing",
"polarity": null,
"sp-act": "bye",
"topic": null,
"utterance": "bye bye"
}
] |
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