Reputation: 884
The LUIS way of doing things, we were able to specify a 'pattern' and get the intents with 100% confidence. And we are trying to get to the same confidence level with the new CLU service. We migrated to CLU from LUIS - but the 'patterns' data got lost in migration as they are not supported in the CLU services.
We are trying to achieve the same with the new CLU service, with a project that would model a 'gather any number' intent.
Attached is a JSON file of the project the we have been trying out with. Trying to get the model to recognize the intent with 100% confidence. But it is not recognizing the intent correctly.
Our goal is to recognize any of the following phrases as a 'gather_number' intent with 100% confidence. The entity value is recognized with 100% accuracy fine. But the intent is not as shown in the 'Actual intent confidence' below.
Any thoughts on what could be done for training the model to get to 100% in all scenarios for 'Actual intent confidence'?
With CLU, here are the findings:
Input | Intent | myNumber entity value | Expected Intent Confidence | Actual intent confidence |
---|---|---|---|---|
1 | gather_number | 1 | 100% | 67.33% |
100 | gather_number | 100 | 100% | 100% |
its 100 | gather_number | 100 | 100% | 100% |
its 3212.44 | gather_number | 3212.44 | 100% | 65.18% |
willing to give 383.22 | gather_number | 383.22 | 100% | 62.24% |
dummy text | None | No entities predicted | 100% | 67.30% |
blah | None | No entities predicted | 100% | 100% |
200 may be | None | No entities predicted | 100% | 76.86% |
Here is the exported CLU project JSON:
{
"projectFileVersion": "2022-10-01-preview",
"stringIndexType": "Utf16CodeUnit",
"metadata": {
"projectKind": "Conversation",
"settings": {
"confidenceThreshold": 0
},
"projectName": "TestNumbers",
"multilingual": false,
"description": "Testing any number",
"language": "en-us"
},
"assets": {
"projectKind": "Conversation",
"intents": [
{
"category": "None"
},
{
"category": "gather_number"
}
],
"entities": [
{
"category": "mynumber",
"compositionSetting": "combineComponents",
"prebuilts": [
{
"category": "Quantity.Number"
}
]
}
],
"utterances": [
{
"text": "oh k 100",
"language": "en-us",
"intent": "gather_number",
"entities": [],
"dataset": "Train"
},
{
"text": "take 100",
"language": "en-us",
"intent": "gather_number",
"entities": [],
"dataset": "Train"
},
{
"text": "100 now 200 later",
"language": "en-us",
"intent": "gather_number",
"entities": [],
"dataset": "Train"
},
{
"text": "only 100",
"language": "en-us",
"intent": "gather_number",
"entities": [],
"dataset": "Train"
},
{
"text": "100 only",
"language": "en-us",
"intent": "gather_number",
"entities": [],
"dataset": "Train"
},
{
"text": "100",
"language": "en-us",
"intent": "gather_number",
"entities": [
{
"category": "mynumber",
"offset": 0,
"length": 3
}
],
"dataset": "Train"
},
{
"text": "this time 100",
"language": "en-us",
"intent": "gather_number",
"entities": [],
"dataset": "Train"
},
{
"text": "no 100",
"language": "en-us",
"intent": "gather_number",
"entities": [],
"dataset": "Train"
},
{
"text": "yes 100",
"language": "en-us",
"intent": "gather_number",
"entities": [],
"dataset": "Train"
},
{
"text": "for now 100",
"language": "en-us",
"intent": "gather_number",
"entities": [],
"dataset": "Train"
},
{
"text": "great 100",
"language": "en-us",
"intent": "gather_number",
"entities": [],
"dataset": "Train"
},
{
"text": "its 100",
"language": "en-us",
"intent": "gather_number",
"entities": [],
"dataset": "Train"
},
{
"text": "it is 100",
"language": "en-us",
"intent": "gather_number",
"entities": [],
"dataset": "Train"
},
{
"text": "ok 100",
"language": "en-us",
"intent": "gather_number",
"entities": [],
"dataset": "Train"
},
{
"text": "how about 100",
"language": "en-us",
"intent": "gather_number",
"entities": [],
"dataset": "Train"
},
{
"text": "got to pay 100",
"language": "en-us",
"intent": "gather_number",
"entities": [],
"dataset": "Train"
},
{
"text": "my number is 100",
"language": "en-us",
"intent": "gather_number",
"entities": [],
"dataset": "Train"
}
]
}
}
Upvotes: 1
Views: 425