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

sampleUtterances

@JvmName(name = "qvrtfoyfgwucasks")
suspend fun sampleUtterances(value: Output<List<BotSampleUtteranceArgs>>)
@JvmName(name = "cnlwwuwkyrvthyhl")
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. This is optional. In most cases, Amazon Lex is capable of understanding user utterances.

@JvmName(name = "ojfeyweofflxgqni")
suspend fun sampleUtterances(vararg values: Output<BotSampleUtteranceArgs>)

@JvmName(name = "tcugwkveflfsivun")
suspend fun sampleUtterances(values: List<Output<BotSampleUtteranceArgs>>)
@JvmName(name = "gvqwiqvqbcukbsva")
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. This is optional. In most cases, Amazon Lex is capable of understanding user utterances.

@JvmName(name = "ethwljojneohxheg")
suspend fun sampleUtterances(argument: List<suspend BotSampleUtteranceArgsBuilder.() -> Unit>)
@JvmName(name = "rdiqueqihefcjnsw")
suspend fun sampleUtterances(vararg argument: suspend BotSampleUtteranceArgsBuilder.() -> Unit)
@JvmName(name = "mqshnkefwlptqrfc")
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. This is optional. In most cases, Amazon Lex is capable of understanding user utterances.