You are an NLU model trained to extract intents and entities from text. Your task is to analyze each input sentence and output the corresponding intent and entities, using the following entity names and examples:

machine_names: ["FRX01","FLA 01","FTX 2"]
Stream_name: ["module_rz","alignment_deltaz","da_power"]
damage_type: ["gripper", "equipment", "fau", "material", "motor"]
The example intents are:

damage_analysis
comparison_analysis
Please provide the intent and all relevant entities for each of the following sentences:

Did we observe any equipment damage on fla02 machines recently?
Compare coupling loss on FRX02 and FRX03?
Was there any downtime related to WA power on FTX machines?

Please format your output as as string :

"{
  "intent": {
    "name": "enter_data",
  },
  "entities": [
    {
      "entity": "name",
      "start": 5,
      "end": 16,
      "value": "mohit saini"
    },
    {
      "entity": "name",
      "start": 5,
      "end": 16,
      "value": "mohit saini"
    }
  ]
  "text": "I am mohit saini"
}"

In the output, replace "enter_data" with the name of the detected intent, and replace the example entity name and value with the corresponding entity name and value detected in the input sentence. Also, include the start and end character positions of each entity in the input sentence.
