NLU Workbench properties
Refer to these system properties for the Natural Language Understanding (NLU) application.
NLU Workbench properties and their usage
To access your system properties, use the admin or nlu_admin role and the following path in the application navigator: All > NLU Workbench > Settings.
| Label and Name | Default value | Plugin | Recommended usage |
|---|---|---|---|
| Maximum number of utterances per intentglide.nlu.utterances_per_intent.value_limit | 200 | NLU Workbench | Use fewer than 200 utterances per intent to keep your model well balanced in terms of intent size.Note: Value must be greater than 5 and less than or equal to 300. |
| Maximum number of records in a Table vocabulary sourceglide.platform_ml.api.max_nlu_lookupsource_records | 100,000 | NLU Workbench | Keep the value under 100,000. |
| Maximum number of values in a List vocabulary sourceglide.nlu.static_lookup.value_limit | 1,000 | NLU Workbench | Keep the value under 1,000. |
| Enable pre-built vocabulary for software namesglide.mlpredictor.option.nlu.@LookupSources:software | enabled | NLU Workbench | Enable pre-built vocabulary so the system can recognize software names. |
| Enable pre-built vocabulary for hardware namesglide.mlpredictor.option.nlu.@LookupSources:hardware | enabled | NLU Workbench | Enable pre-built vocabulary so the system can recognize hardware names. |
| Label and Name | Default value | Plugin | Recommended usage |
|---|---|---|---|
| Maximum number of records for Intent Discovery classificationsn_nlu_discovery.intent_discovery_max_classification_limit | 300,000 | Intent Discovery | Keep the number of records less than 500,000. |
| Minimum number of records for Intent Discovery classificationsn_nlu_discovery.intent_discovery_min_classification_limit | 10,000 | Intent Discovery | Use at least 10,000 records to get high quality results. |
| Minimum number of records for NLU performance analysissn_nlu_workbench.glide.nlu.performance.min_clustering_records | 5,000 | NLU Workbench - Advanced Features | Use at least 5,000 records to get high quality results. |
| NLU Conflict Detection - Moderate Thresholdsn_nlu_workbench.glide.nlu.conflict.moderate_threshold | .85 | NLU Workbench - Advanced Features | Must be a decimal between 0 and 1. Keep this threshold less than the Critical Threshold. |
| NLU Conflict Detection - Critical Thresholdsn_nlu_workbench.glide.nlu.conflict.critical_threshold | .95 | NLU Workbench - Advanced Features | Must be a decimal between 0 and 1. Keep this threshold greater than the Moderate Threshold. |
| The maximum number of rows in a batch test import filesn_nlu_workbench.glide.nlu.batch_test.max_import_rows | 10,000 | NLU Workbench - Advanced Features | Make sure your batch test import file has no more than 10,000 rows. |
| The maximum number of utterances to display for feedback in the expert feedback loopglide.mlpredictor.option.nlu.activeLearning.label_candidate_table.max_response_size | 300 | NLU Workbench - Advanced Features | Pull no more than 300 utterances from your users' Virtual Agent chat logs to display for feedback in the Expert Feedback Loop application.The minimum umber of utterances a user should review before tuning the model |
| The minimum number of utterances a user should review before tuning the modelsn_nlu_workbench.glide.nlu.optimize.min_labeled_data | 100 | NLU Workbench - Advanced Features | Provide and save feedback for at least 100 utterances from your users' Virtual Agent chat logs so you can execute the Tune Model feature in the Expert Feedback Loop application. |
| The maximum number of records to fetch from Virtual Agent chat logsglide.mlpredictor.option.nlu.activeLearning.va_chat_logs.max_row_limit - 3000 | 3,000 | NLU Workbench - Advanced Features | If there is high NLU usage, increasing the default value to a maximum of 50,000 records will increase the data available for the active learning job to filter up on and display in the Expert Feedback Loop application to give feedback on. |
| Size limit on Label Candidate Table (used for pruning the table)glide.mlpredictor.option.nlu.activeLearning.label_candidate_table.max_data_size - 10000 | 10,000 | NLU Workbench - Advanced Features | The recommended usage for this property is the same as the property above. |
| Size limit on Labeled Data Table (used for pruning the table)glide.mlpredictor.option.nlu.activeLearning.label_table.max_data_size - 10000 | 10,000 | NLU Workbench - Advanced Features | The recommended usage for this property is the same as the property above. |
| Enable this property to unblock your instance during NLU model training. The training will be scheduled for an off-peak time, and we will notify you when it's done. glide.mlpredictor.scheduled.nlu.model.training | False | NLU Workbench - Advanced Features | False |
To get more feedback data from Virtual Agent (VA) chat logs, refer to the Procuring additional VA feedback data on demand section in the Expert Feedback Loop documentation.