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stringclasses 3
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listlengths 1
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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": "5",
"utterances": [
"we need to get a ticket for him from Boston"
]
} | [
{
"mode": "report-constrain-decl",
"polarity": "positive",
"sp-act": "state",
"topic": "location_US-location-from",
"utterance": "we need to get a ticket for him from Boston"
}
] |
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": "6",
"utterances": [
"this is a new reservation"
]
} | [
{
"mode": "query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": null,
"utterance": "this is a new reservation"
}
] |
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": "7",
"utterances": [
"new reservation on June 21"
]
} | [
{
"mode": "partial-decl",
"polarity": "positive",
"sp-act": "answer-refer",
"topic": "month",
"utterance": "new reservation on June 21"
}
] |
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": "8",
"utterances": [
"ok",
"let me let me pull up his profile first"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "decl-disflu",
"polarity": "positive",
"sp-act": "hold",
"topic": null,
"utterance": "let me let me pull up his profile 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": "9",
"utterances": [
"ok",
"and he is um"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "interruption",
"polarity": "positive",
"sp-act": "abandon",
"topic": null,
"utterance": "and he is 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": [
"he wants to fl... he wants to fly from Boston"
]
} | [
{
"mode": "preference3-decl",
"polarity": "positive",
"sp-act": "expressWish",
"topic": "location_US-location-from",
"utterance": "he wants to fl... he wants to fly from Boston"
}
] |
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": [
"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": "12",
"utterances": [
"to Baltimore Washington International on flight",
"i'm sure it's Piedmont P L P I"
]
} | [
{
"mode": "partial-decl",
"polarity": "positive",
"sp-act": "refer",
"topic": "location-to-location_US-district_US",
"utterance": "to Baltimore Washington International on flight"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": "location_US",
"utterance": "i'm sure it's Piedmont P L P I"
}
] |
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": [
"P I",
"at what time"
]
} | [
{
"mode": null,
"polarity": "positive",
"sp-act": "echo",
"topic": null,
"utterance": "P I"
},
{
"mode": "query-open-query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": "time",
"utterance": "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": "14",
"utterances": [
"uh",
"7:40 p m"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "hesitate",
"topic": null,
"utterance": "uh"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "answer-refer",
"topic": "enum",
"utterance": "7:40 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": "15",
"utterances": [
"and this is on the 21st of June"
]
} | [
{
"mode": "query",
"polarity": "positive",
"sp-act": "reqConfirm",
"topic": "month",
"utterance": "and this is on the 21st 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": "16",
"utterances": [
"yeah",
"arriving 9:01 p m"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "confirm-acknowledge",
"topic": null,
"utterance": "yeah"
},
{
"mode": "partial-decl",
"polarity": "positive",
"sp-act": "elab-refer",
"topic": "enum-arrival",
"utterance": "arriving 9:01 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": "17",
"utterances": [
"ok",
"that's Piedmont 1 9 0 9 on the 21 of June"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "query",
"polarity": "positive",
"sp-act": "reqConfirm",
"topic": "enum-location_US-month",
"utterance": "that's Piedmont 1 9 0 9 on the 21 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": "18",
"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 (agent_A). | {
"speaker": "agent_A",
"turn": "19",
"utterances": [
"departing Boston 7:40 p m",
"arriving Baltimore 9:01 p m"
]
} | [
{
"mode": "partial-decl",
"polarity": "positive",
"sp-act": "refer",
"topic": "location_US-location-enum",
"utterance": "departing Boston 7:40 p m"
},
{
"mode": "partial-decl",
"polarity": "positive",
"sp-act": "refer",
"topic": "location_US-location-enum-arrival",
"utterance": "arriving Baltimore 9:01 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": "20",
"utterances": [
"right",
"and then he wants to return from um Baltimore Washington to San Francisco on the 23rd of June",
"and he requests flight 3 2 3 TWA",
"actually",
"it's two flight numbers",
"it's 3 2 3",
"and then it changes to 7 5 1 at 5:16 in the afternoon"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "right"
},
{
"mode": "preference3-decl",
"polarity": "positive",
"sp-act": "expressWish",
"topic": "location-location_US-from-district_US",
"utterance": "and then he wants to return from um Baltimore Washington to San Francisco on the 23rd of June"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": "enum",
"utterance": "and he requests flight 3 2 3 TWA"
},
{
"mode": "report-constrain",
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "actually"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "state",
"topic": "number",
"utterance": "it's two flight numbers"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "state",
"topic": "enum",
"utterance": "it's 3 2 3"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "state",
"topic": "enum-time",
"utterance": "and then it changes to 7 5 1 at 5:16 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": "21",
"utterances": [
"ok",
"one moment",
"this is to San Jose did you say"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": null,
"polarity": null,
"sp-act": "hold",
"topic": null,
"utterance": "one moment"
},
{
"mode": "tag-query",
"polarity": "positive",
"sp-act": "reqConfirm",
"topic": "to-location_US",
"utterance": "this is to San Jose did you say"
}
] |
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": [
"i understand it's to San Francisco",
"TWA flight 3 2 3 slash 7 5 1"
]
} | [
{
"mode": "awareness-constrain-decl",
"polarity": "positive",
"sp-act": "correct",
"topic": "to-location_US",
"utterance": "i understand it's to San Francisco"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "elab-refer",
"topic": "enum",
"utterance": "TWA flight 3 2 3 slash 7 5 1"
}
] |
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": [
"3 2 3 and 7 5 1",
"ok",
"and then does he know there is a non-stop that goes from Dulles to San Francisco instead of connection through St Louis"
]
} | [
{
"mode": "decl",
"polarity": "positive",
"sp-act": "echo",
"topic": "enum",
"utterance": "3 2 3 and 7 5 1"
},
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "exists-constrain-closed-query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": "airport_US-to-location_US-from",
"utterance": "and then does he know there is a non-stop that goes from Dulles to San Francisco instead of connection through St Louis"
}
] |
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": [
"i think he's aware of it",
"but i think we picked this one because um he could get the business traveller uh seating"
]
} | [
{
"mode": "opinion-decl",
"polarity": "positive",
"sp-act": "answer-state",
"topic": null,
"utterance": "i think he's aware of it"
},
{
"mode": "poss3-report-opinion-reason-constrain-decl",
"polarity": "positive",
"sp-act": "elab-expressOpinion-stateReason",
"topic": "number",
"utterance": "but i think we picked this one because um he could get the business traveller uh seating"
}
] |
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": [
"he can also he can also get that on the non-stop"
]
} | [
{
"mode": "poss3-decl",
"polarity": "positive",
"sp-act": "expressPossibility",
"topic": null,
"utterance": "he can also he can also get that on the non-stop"
}
] |
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": [
"on the non-stop",
"and what is the",
"uh",
"give me the times for the non-stop"
]
} | [
{
"mode": "partial-frag",
"polarity": "positive",
"sp-act": "echo-refer",
"topic": null,
"utterance": "on the non-stop"
},
{
"mode": "open-abandon",
"polarity": "positive",
"sp-act": "reqInfo-abandon",
"topic": null,
"utterance": "and what is the"
},
{
"mode": null,
"polarity": null,
"sp-act": "hesitate",
"topic": null,
"utterance": "uh"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "direct",
"topic": null,
"utterance": "give me the times for the non-stop"
}
] |
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",
"one moment",
"the non-stop is at 4:40 arriving 7:05"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": null,
"polarity": null,
"sp-act": "hold",
"topic": null,
"utterance": "one moment"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": "time-enum-arrival",
"utterance": "the non-stop is at 4:40 arriving 7:05"
}
] |
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": [
"se... 4:40 to 7:05"
]
} | [
{
"mode": "decl",
"polarity": "positive",
"sp-act": "echo",
"topic": "enum",
"utterance": "se... 4:40 to 7:05"
}
] |
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": [
"into San Francisco",
"it's a non-stop from Dulles to San Francisco",
"maybe he can't leave that early"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "refer",
"topic": "to",
"utterance": "into San Francisco"
},
{
"mode": "partial-decl",
"polarity": "positive",
"sp-act": "state",
"topic": "location_US-airport_US-to-from",
"utterance": "it's a non-stop from Dulles to San Francisco"
},
{
"mode": "poss3-opinion",
"polarity": "negative",
"sp-act": "expressImPossibility",
"topic": "time",
"utterance": "maybe he can't leave that early"
}
] |
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": [
"i don't know",
"uh",
"let me",
"can i make the reservation and and change it by tomorrow"
]
} | [
{
"mode": "report-nonawareness-frag",
"polarity": "negative",
"sp-act": "expressNonAwareness",
"topic": null,
"utterance": "i don't know"
},
{
"mode": null,
"polarity": null,
"sp-act": "hesitate",
"topic": null,
"utterance": "uh"
},
{
"mode": "abandon",
"polarity": "positive",
"sp-act": "direct-abandon",
"topic": null,
"utterance": "let me"
},
{
"mode": "closed",
"polarity": "positive",
"sp-act": "reqOpt",
"topic": "day",
"utterance": "can i make the reservation and and change it by tomorrow"
}
] |
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": [
"sure",
"if it's it's still available",
"right"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "stateOpt-agree",
"topic": null,
"utterance": "sure"
},
{
"mode": "condition-decl-disflu",
"polarity": "positive",
"sp-act": "elab-stateCondition",
"topic": "availability",
"utterance": "if it's it's still available"
},
{
"mode": null,
"polarity": null,
"sp-act": "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": "32",
"utterances": [
"yeah",
"i know subject to availability",
"i'm sorry",
"i've been giving you quick numbers here"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "yeah"
},
{
"mode": "awareness-constrain-decl",
"polarity": "positive",
"sp-act": "expressAwareness",
"topic": "availability",
"utterance": "i know subject to availability"
},
{
"mode": "regret",
"polarity": null,
"sp-act": "apologise",
"topic": null,
"utterance": "i'm sorry"
},
{
"mode": "report-decl",
"polarity": "positive",
"sp-act": "state",
"topic": "number",
"utterance": "i've been giving you quick numbers 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": "33",
"utterances": [
"it's ok"
]
} | [
{
"mode": "reassurance-tag-decl",
"polarity": "positive",
"sp-act": "approve",
"topic": null,
"utterance": "it's 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": "34",
"utterances": [
"it's all right",
"let me just check the um"
]
} | [
{
"mode": "reassurance-tag",
"polarity": "positive",
"sp-act": "approve",
"topic": null,
"utterance": "it's all right"
},
{
"mode": "hold-interruption",
"polarity": "positive",
"sp-act": "hold-abandon",
"topic": "verify",
"utterance": "let me just check the 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 (agent_A). | {
"speaker": "agent_A",
"turn": "35",
"utterances": [
"and now",
"lets see what kind of fares they have",
"a three day advance purchase fare",
"using the business class upgrade of 4 4 9 one way"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "and now"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "hold",
"topic": null,
"utterance": "lets see what kind of fares they have"
},
{
"mode": "frag",
"polarity": "positive",
"sp-act": "refer",
"topic": "number-day-duration",
"utterance": "a three day advance purchase fare"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": "enum-number",
"utterance": "using the business class upgrade of 4 4 9 one 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": "36",
"utterances": [
"i was quoted 6 0 8 50 for the whole round f... from Boston to Washington",
"from Washington um to San Francisco"
]
} | [
{
"mode": "report-frag",
"polarity": "positive",
"sp-act": "state",
"topic": "enum-location-to-location_US-from-district_US",
"utterance": "i was quoted 6 0 8 50 for the whole round f... from Boston to Washington"
},
{
"mode": "partial-decl",
"polarity": "positive",
"sp-act": "refer",
"topic": "to-location_US-location-from-district_US",
"utterance": "from Washington um to San Francisco"
}
] |
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": [
"now",
"this portion was for Baltimore San Francisco only",
"ok",
"let me just see what"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "now"
},
{
"mode": "constrain-decl",
"polarity": "positive",
"sp-act": "state",
"topic": "location_US-location",
"utterance": "this portion was for Baltimore San Francisco only"
},
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "query-hold-abandon",
"polarity": "positive",
"sp-act": "hold-abandon",
"topic": null,
"utterance": "let me just see what"
}
] |
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": [
"could you find out how much the fare is all total"
]
} | [
{
"mode": "query-query",
"polarity": "positive",
"sp-act": "direct-reqInfo",
"topic": null,
"utterance": "could you find out how much the fare is all total"
}
] |
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": [
"ok",
"it's 6 0 8 50 that has to be ticketed by the 15th of June",
"there are no cancellation or change penalties",
"if any changes are made",
"it's just subject to whatever the new fare is"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": "enum-month-date",
"utterance": "it's 6 0 8 50 that has to be ticketed by the 15th of June"
},
{
"mode": "alternative-exists-frag",
"polarity": "negative",
"sp-act": "state",
"topic": "location-cancel",
"utterance": "there are no cancellation or change penalties"
},
{
"mode": "constrain-condition-decl",
"polarity": "positive",
"sp-act": "stateCondition",
"topic": null,
"utterance": "if any changes are made"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "state",
"topic": "fare",
"utterance": "it's just subject to whatever the new fare is"
}
] |
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": [
"sure"
]
} | [
{
"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 (agent_A). | {
"speaker": "agent_A",
"turn": "41",
"utterances": [
"ok",
"it has to be ticketed by the15th of June"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "ok"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "stateConstraint",
"topic": "month-date",
"utterance": "it has to be ticketed by the15th 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": "42",
"utterances": [
"all right"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "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": "43",
"utterances": [
"there are no penalties for cancellation if changes are made",
"it's subject to whatever the new fares are at that time"
]
} | [
{
"mode": "exists-condition-decl",
"polarity": "negative",
"sp-act": "state",
"topic": "location-cancel",
"utterance": "there are no penalties for cancellation if changes are made"
},
{
"mode": "constrain-decl",
"polarity": "positive",
"sp-act": "state",
"topic": "time",
"utterance": "it's subject to whatever the new fares are at that 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": "44",
"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": "45",
"utterances": [
"cos they're going to increase the fare"
]
} | [
{
"mode": "reason-decl",
"polarity": "positive",
"sp-act": "stateReason",
"topic": null,
"utterance": "cos they're going to increase the fare"
}
] |
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": [
"but there's no penalty existing"
]
} | [
{
"mode": "exists-constrain-query",
"polarity": "negative",
"sp-act": "reqConfirm",
"topic": null,
"utterance": "but there's no penalty existing"
}
] |
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": [
"there's no penalty uh if it's cancelled",
"no"
]
} | [
{
"mode": "exists-condition-decl",
"polarity": "negative",
"sp-act": "confirm-state",
"topic": "cancel",
"utterance": "there's no penalty uh if it's cancelled"
},
{
"mode": null,
"polarity": null,
"sp-act": "negate",
"topic": null,
"utterance": "no"
}
] |
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": [
"yeah",
"the non-stop flight seems to be more appealing to me",
"i mean",
"this man travels so much though",
"let me check with him um"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "yeah"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "expressOpinion",
"topic": null,
"utterance": "the non-stop flight seems to be more appealing to me"
},
{
"mode": null,
"polarity": null,
"sp-act": "phatic",
"topic": null,
"utterance": "i mean"
},
{
"mode": "constrain-decl",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "this man travels so much though"
},
{
"mode": "hold-decl",
"polarity": "positive",
"sp-act": "suggest",
"topic": "verify",
"utterance": "let me check with him 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 (agent_A). | {
"speaker": "agent_A",
"turn": "49",
"utterances": [
"ok",
"so",
"what",
"so",
"we're going to hold",
"we'll just go ahead and hold the um"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "so"
},
{
"mode": "open",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": null,
"utterance": "what"
},
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "so"
},
{
"mode": "intent-query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": null,
"utterance": "we're going to hold"
},
{
"mode": "intent-interruption",
"polarity": "positive",
"sp-act": "reqInfo-abandon",
"topic": null,
"utterance": "we'll just go ahead and hold the 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": "50",
"utterances": [
"hold that TWA",
"then i will inform him of the Dulles flight at fou... 4:40",
"leaving uh Dulles and arriving",
"is it San Francisco at 7:05 or San Jose"
]
} | [
{
"mode": null,
"polarity": "positive",
"sp-act": "answer-state-complete",
"topic": null,
"utterance": "hold that TWA"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "elab-state",
"topic": "airport_US-time",
"utterance": "then i will inform him of the Dulles flight at fou... 4:40"
},
{
"mode": "partial",
"polarity": "positive",
"sp-act": "state",
"topic": "airport_US-arrival",
"utterance": "leaving uh Dulles and arriving"
},
{
"mode": "alternative-closed-query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": "location_US-time-enum",
"utterance": "is it San Francisco at 7:05 or San Jose"
}
] |
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": [
"it's San Francisco"
]
} | [
{
"mode": "decl",
"polarity": "positive",
"sp-act": "answer-state",
"topic": "location_US",
"utterance": "it's San Francisco"
}
] |
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": [
"San Francisco",
"that's what he wants",
"ok"
]
} | [
{
"mode": "partial-frag",
"polarity": "positive",
"sp-act": "echo-refer",
"topic": "location_US",
"utterance": "San Francisco"
},
{
"mode": "preference3-decl",
"polarity": "positive",
"sp-act": "expressWish",
"topic": null,
"utterance": "that's what he wants"
},
{
"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": "53",
"utterances": [
"it's still 6:08 any which way we do this",
"i'm just thinking the convenience of the traveller"
]
} | [
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": "enum",
"utterance": "it's still 6:08 any which way we do this"
},
{
"mode": "hold-decl",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "i'm just thinking the convenience of the traveller"
}
] |
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": "54",
"utterances": [
"on the non-stop",
"let me see",
"i think you get that same fare",
"let me check the fares"
]
} | [
{
"mode": "partial-frag",
"polarity": "positive",
"sp-act": "refer",
"topic": null,
"utterance": "on the non-stop"
},
{
"mode": null,
"polarity": null,
"sp-act": "hold",
"topic": null,
"utterance": "let me see"
},
{
"mode": "opinion-decl",
"polarity": "positive",
"sp-act": "expressOpinion",
"topic": null,
"utterance": "i think you get that same fare"
},
{
"mode": "hold-decl",
"polarity": "positive",
"sp-act": "hold",
"topic": "verify",
"utterance": "let me check the fares"
}
] |
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": "55",
"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": "56",
"utterances": [
"i think it that would have to be using a 25 percent penalty on TWA",
"yeah",
"it would be 20 dollars more if he wanted to have a fare without a penalty"
]
} | [
{
"mode": "opinion-constrain-decl",
"polarity": "positive",
"sp-act": "expressOpinion",
"topic": "enum",
"utterance": "i think it that would have to be using a 25 percent penalty on TWA"
},
{
"mode": null,
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "yeah"
},
{
"mode": "opinion-preference3-condition-decl",
"polarity": "positive",
"sp-act": "expressOpinion",
"topic": "enum",
"utterance": "it would be 20 dollars more if he wanted to have a fare without a penalty"
}
] |
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": "57",
"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": "58",
"utterances": [
"because the Dulles non-stop",
"to get that 449",
"you have to take a 25 percent penalty fare",
"if you don't",
"then it's 469",
"so it would increase that total fare by 20 dollars"
]
} | [
{
"mode": "reason-constrain",
"polarity": "positive",
"sp-act": "stateReason",
"topic": "enum-airport_US",
"utterance": "because the Dulles non-stop"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "to get that 449"
},
{
"mode": "",
"polarity": "positive",
"sp-act": "state",
"topic": "penalty",
"utterance": "you have to take a 25 percent penalty fare"
},
{
"mode": "condition-decl",
"polarity": "negative",
"sp-act": "stateCondition",
"topic": null,
"utterance": "if you don't"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "then it's 469"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": "enum",
"utterance": "so it would increase that total fare by 20 dollars"
}
] |
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": "59",
"utterances": [
"so",
"it's 608 plus 20"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "so"
},
{
"mode": "query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": "enum",
"utterance": "it's 608 plus 20"
}
] |
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": "60",
"utterances": [
"right",
"if he wanted to go without a penalty",
"it's 6 plus 20"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "answer-acknowledge",
"topic": null,
"utterance": "right"
},
{
"mode": "preference3-condition",
"polarity": "positive",
"sp-act": "elab-stateCondition",
"topic": "enum",
"utterance": "if he wanted to go without a penalty"
},
{
"mode": "",
"polarity": "positive",
"sp-act": "state",
"topic": "",
"utterance": "it's 6 plus 20"
}
] |
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": "61",
"utterances": [
"he needs the cheapest rate possible on this one",
"um so",
"let me talk it over with him uh"
]
} | [
{
"mode": "constrain-decl",
"polarity": "positive",
"sp-act": "stateConstraint",
"topic": "number",
"utterance": "he needs the cheapest rate possible on this one"
},
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "um so"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "suggest",
"topic": null,
"utterance": "let me talk it over with him 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": "62",
"utterances": [
"okay then",
"on the business class",
"that would be row nine seat number five",
"which is an aisle seat",
"now",
"what what about",
"how's he getting to Boston"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "okay then"
},
{
"mode": "partial-frag",
"polarity": "positive",
"sp-act": "refer",
"topic": "number",
"utterance": "on the business class"
},
{
"mode": "",
"polarity": "positive",
"sp-act": "predict",
"topic": "",
"utterance": "that would be row nine seat number five"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "which is an aisle seat"
},
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "now"
},
{
"mode": "",
"polarity": "",
"sp-act": "reqInfo-abandon",
"topic": "",
"utterance": "what what about"
},
{
"mode": "closed",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": "to-location_US-location",
"utterance": "how's he getting to Boston"
}
] |
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": "63",
"utterances": [
"he's already purchased his ticket"
]
} | [
{
"mode": "decl",
"polarity": "positive",
"sp-act": "answer-state",
"topic": null,
"utterance": "he's already purchased his ticket"
}
] |
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": "64",
"utterances": [
"ok",
"so",
"this is just all one way travel"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "so"
},
{
"mode": "query",
"polarity": "positive",
"sp-act": "reqConfirm",
"topic": "number",
"utterance": "this is just all one way travel"
}
] |
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": "65",
"utterances": [
"one way travel",
"right"
]
} | [
{
"mode": "tag-decl",
"polarity": "positive",
"sp-act": "confirm",
"topic": "number",
"utterance": "one way travel"
},
{
"mode": null,
"polarity": null,
"sp-act": "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": "66",
"utterances": [
"ok",
"so",
"that was available",
"and i requested that",
"B",
"anything else i can help you with"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "so"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "state",
"topic": "availability",
"utterance": "that was available"
},
{
"mode": "report-decl",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "and i requested that"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "refer",
"topic": null,
"utterance": "B"
},
{
"mode": "poss1-query",
"polarity": "positive",
"sp-act": "reqDirect",
"topic": null,
"utterance": "anything else i can 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": "67",
"utterances": [
"i'll call you back on the Dulles non-stop flight so we'll"
]
} | [
{
"mode": "intent-interruption",
"polarity": "positive",
"sp-act": "answer-state-abandon",
"topic": "airport_US",
"utterance": "i'll call you back on the Dulles non-stop flight so we'll"
}
] |
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": "68",
"utterances": [
"if if he needs that right"
]
} | [
{
"mode": "condition-tag-constrain-decl",
"polarity": "positive",
"sp-act": "reqConfirm",
"topic": null,
"utterance": "if if he needs that 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": "69",
"utterances": [
"if he needs that",
"and if he does get that",
"he has to pay uh 20 dollars more"
]
} | [
{
"mode": "constrain-condition-decl",
"polarity": "positive",
"sp-act": "confirm-stateConstraint",
"topic": null,
"utterance": "if he needs that"
},
{
"mode": "condition",
"polarity": "positive",
"sp-act": "elab-stateCondition",
"topic": null,
"utterance": "and if he does get that"
},
{
"mode": "query",
"polarity": "positive",
"sp-act": "reqConfirm",
"topic": "enum",
"utterance": "he has to pay uh 20 dollars more"
}
] |
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": "70",
"utterances": [
"if he wants to take a fare without a penalty",
"right"
]
} | [
{
"mode": "preference3-condition",
"polarity": "positive",
"sp-act": "confirm-stateCondition",
"topic": null,
"utterance": "if he wants to take a fare without a penalty"
},
{
"mode": null,
"polarity": null,
"sp-act": "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": "71",
"utterances": [
"a fare without a penalty"
]
} | [
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "a fare without a penalty"
}
] |
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": "72",
"utterances": [
"if he's willing to take it with a penalty",
"it would be exactly the same fare"
]
} | [
{
"mode": "condition",
"polarity": "positive",
"sp-act": "stateCondition",
"topic": null,
"utterance": "if he's willing to take it with a penalty"
},
{
"mode": "opinion-decl",
"polarity": "positive",
"sp-act": "predict",
"topic": null,
"utterance": "it would be exactly the same fare"
}
] |
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": "73",
"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": "74",
"utterances": [
"ok now"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok 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 (caller). | {
"speaker": "caller",
"turn": "75",
"utterances": [
"i i hesitate uh for him particularly to get anything uh because he does change a lot"
]
} | [
{
"mode": "reason-decl-disflu",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "i i hesitate uh for him particularly to get anything uh because he does change 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": "76",
"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": "77",
"utterances": [
"so i i'd rather get the 20 dollars",
"but we'll see what he says"
]
} | [
{
"mode": "preference1-frag-disflu",
"polarity": "positive",
"sp-act": "state",
"topic": "enum",
"utterance": "so i i'd rather get the 20 dollars"
},
{
"mode": "intent-report-constrain-decl",
"polarity": "positive",
"sp-act": "stateIntent",
"topic": null,
"utterance": "but we'll see what he says"
}
] |
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": "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 (caller). | {
"speaker": "caller",
"turn": "79",
"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": "80",
"utterances": [
"all right",
"thanks",
"B"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "all right"
},
{
"mode": "thank",
"polarity": null,
"sp-act": "thank",
"topic": null,
"utterance": "thanks"
},
{
"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": "81",
"utterances": [
"you are A right"
]
} | [
{
"mode": "tag-query",
"polarity": "positive",
"sp-act": "reqConfirm",
"topic": null,
"utterance": "you are A 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": "82",
"utterances": [
"yeah",
"i'm A all right"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "confirm-acknowledge",
"topic": null,
"utterance": "yeah"
},
{
"mode": "intro-tag-decl",
"polarity": "positive",
"sp-act": "elab-identifySelf",
"topic": null,
"utterance": "i'm A 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 (caller). | {
"speaker": "caller",
"turn": "83",
"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": "84",
"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",
"can 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": "can 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": [
"oh",
"yes",
"A",
"this is B"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "exclaim",
"topic": null,
"utterance": "oh"
},
{
"mode": null,
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "yes"
},
{
"mode": null,
"polarity": "positive",
"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",
"thanks",
"what can i help you with"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "thank",
"polarity": null,
"sp-act": "thank",
"topic": null,
"utterance": "thanks"
},
{
"mode": "open-query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": null,
"utterance": "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": [
"well",
"C is going to go to Ottawa"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "well"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "answer-state",
"topic": "to-location_int",
"utterance": "C is going to go to Ottawa"
}
] |
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": [
"is this for a new reservation"
]
} | [
{
"mode": "closed-query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": null,
"utterance": "is this for a new reservation"
}
] |
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": [
"yes",
"and i",
"what i need right now are um choices"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "answer-acknowledge",
"topic": null,
"utterance": "yes"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "abandon",
"topic": null,
"utterance": "and i"
},
{
"mode": "report-constrain-decl",
"polarity": "positive",
"sp-act": "state",
"topic": null,
"utterance": "what i need right now are um choices"
}
] |
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": [
"just flight information then"
]
} | [
{
"mode": "partial-query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": null,
"utterance": "just flight information then"
}
] |
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": [
"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": "9",
"utterances": [
"ok",
"and what date is he gonna go"
]
} | [
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "open-query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": "date",
"utterance": "and what date is he gonna go"
}
] |
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": [
"the 22nd",
"and he needs to be there in time for an evening meeting if he can be",
"say around 6 o'clock"
]
} | [
{
"mode": null,
"polarity": "positive",
"sp-act": "answer-refer",
"topic": null,
"utterance": "the 22nd"
},
{
"mode": "poss3-constrain-condition-decl",
"polarity": "positive",
"sp-act": "elab-stateConstraint",
"topic": "time-location",
"utterance": "and he needs to be there in time for an evening meeting if he can be"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "suggest",
"topic": "time-enum",
"utterance": "say around 6 o'clock"
}
] |
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": [
"let me see here"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "let me see 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": "12",
"utterances": [
"22nd of June",
"did i make that clear"
]
} | [
{
"mode": null,
"polarity": "positive",
"sp-act": "refer",
"topic": "month",
"utterance": "22nd of June"
},
{
"mode": "closed-query",
"polarity": "positive",
"sp-act": "reqConfirm",
"topic": null,
"utterance": "did i make that clear"
}
] |
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": [
"yeah",
"a... i assumed that",
"yeah",
"eh",
"there's nothing really that gets in that early",
"uh",
"Air Canada has a connection through Toronto that leaves San Francisco at 7:50 a m",
"arrives Toronto at 3:35",
"but the connection to Ottawa doesn't leave until 5:15",
"getting into Ottawa at 6:10 and"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "confirm-acknowledge",
"topic": null,
"utterance": "yeah"
},
{
"mode": "report-opinion-decl-disflu",
"polarity": "positive",
"sp-act": "elab-abandon",
"topic": null,
"utterance": "a... i assumed that"
},
{
"mode": null,
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "yeah"
},
{
"mode": null,
"polarity": null,
"sp-act": "hesitate",
"topic": null,
"utterance": "eh"
},
{
"mode": "exists-decl",
"polarity": "negative",
"sp-act": "state",
"topic": "time",
"utterance": "there's nothing really that gets in that early"
},
{
"mode": null,
"polarity": null,
"sp-act": "hesitate",
"topic": null,
"utterance": "uh"
},
{
"mode": "frag",
"polarity": "positive",
"sp-act": "state",
"topic": "location_US-time-enum-location_int",
"utterance": "Air Canada has a connection through Toronto that leaves San Francisco at 7:50 a m"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": "time-location_int-arrival",
"utterance": "arrives Toronto at 3:35"
},
{
"mode": "constrain-frag",
"polarity": "negative",
"sp-act": "state",
"topic": "to-location_int",
"utterance": "but the connection to Ottawa doesn't leave until 5:15"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "state",
"topic": "time-enum-location_int",
"utterance": "getting into Ottawa at 6:10 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 (caller). | {
"speaker": "caller",
"turn": "14",
"utterances": [
"when"
]
} | [
{
"mode": "query-exclaim-partial",
"polarity": "positive",
"sp-act": "reqConfirm",
"topic": "time",
"utterance": "when"
}
] |
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": [
"that's about the earliest one"
]
} | [
{
"mode": "decl",
"polarity": "positive",
"sp-act": "confirm-state",
"topic": "number-time",
"utterance": "that's about the earliest 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": "16",
"utterances": [
"um",
"ok"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "hesitate",
"topic": null,
"utterance": "um"
},
{
"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": [
"other than leaving the evening before",
"i mean",
"the",
"you know",
"like just after midnight"
]
} | [
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": "time",
"utterance": "other than leaving the evening before"
},
{
"mode": null,
"polarity": null,
"sp-act": "phatic",
"topic": null,
"utterance": "i mean"
},
{
"mode": null,
"polarity": "positive",
"sp-act": "abandon",
"topic": null,
"utterance": "the"
},
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "you know"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "state",
"topic": "time",
"utterance": "like just after midnight"
}
] |
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": [
"so",
"we have one tha... on Air Canada that goes to Toronto huh"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "init",
"topic": null,
"utterance": "so"
},
{
"mode": "tag-query",
"polarity": "positive",
"sp-act": "reqConfirm",
"topic": "to-number-location_int",
"utterance": "we have one tha... on Air Canada that goes to Toronto 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": "19",
"utterances": [
"right",
"and then it's a change of planes there",
"but it doesn't arrive into Ottawa until 6:10"
]
} | [
{
"mode": null,
"polarity": null,
"sp-act": "confirm-acknowledge",
"topic": null,
"utterance": "right"
},
{
"mode": "decl",
"polarity": "positive",
"sp-act": "elab-state",
"topic": "location",
"utterance": "and then it's a change of planes there"
},
{
"mode": "constrain-decl",
"polarity": "negative",
"sp-act": "state",
"topic": "location_int-arrival",
"utterance": "but it doesn't arrive into Ottawa until 6:10"
}
] |
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": [
"let me take all that down anyway",
"ok",
"i guess it's too",
"at what time does it get to Toronto"
]
} | [
{
"mode": "decl",
"polarity": "positive",
"sp-act": "hold",
"topic": null,
"utterance": "let me take all that down anyway"
},
{
"mode": "tag",
"polarity": null,
"sp-act": "acknowledge",
"topic": null,
"utterance": "ok"
},
{
"mode": "opinion-reject-decl",
"polarity": "positive",
"sp-act": "reject-abandon",
"topic": null,
"utterance": "i guess it's too"
},
{
"mode": "open-query",
"polarity": "positive",
"sp-act": "reqInfo",
"topic": "time-to-location_int",
"utterance": "at what time does it get to Toronto"
}
] |
Subsets and Splits