pulumi-aws-native-kotlin/com.pulumi.awsnative.lex.kotlin.inputs/BotSlotValueElicitationSettingArgsBuilder/sampleUtterances

sampleUtterances

@JvmName(name = "tgeeupdboeycvguv")

suspend fun sampleUtterances(value: Output<List<BotSampleUtteranceArgs>>)

@JvmName(name = "gfgevgjhkmkjyfwv")

suspend fun sampleUtterances(value: List<BotSampleUtteranceArgs>?)

Parameters

value

If you know a specific pattern that users might respond to an Amazon Lex request for a slot value, you can provide those utterances to improve accuracy.

@JvmName(name = "rcjgjxurphxfiwyx")

suspend fun sampleUtterances(vararg values: Output<BotSampleUtteranceArgs>)

@JvmName(name = "fnkldiolojyvwypg")

suspend fun sampleUtterances(values: List<Output<BotSampleUtteranceArgs>>)

@JvmName(name = "uggmugrhqtymawit")

suspend fun sampleUtterances(vararg values: BotSampleUtteranceArgs)

Parameters

values

If you know a specific pattern that users might respond to an Amazon Lex request for a slot value, you can provide those utterances to improve accuracy.

@JvmName(name = "sbrqxnlmootcrtuj")

suspend fun sampleUtterances(argument: List<suspend BotSampleUtteranceArgsBuilder.() -> Unit>)

@JvmName(name = "nsaglpxsifstpixx")

suspend fun sampleUtterances(vararg argument: suspend BotSampleUtteranceArgsBuilder.() -> Unit)

@JvmName(name = "woyuqmklnmbhrggn")

suspend fun sampleUtterances(argument: suspend BotSampleUtteranceArgsBuilder.() -> Unit)

Parameters

argument

If you know a specific pattern that users might respond to an Amazon Lex request for a slot value, you can provide those utterances to improve accuracy.