--- sourceDocument: Xanadu Enable AI sourceDocumentLink: https://servicenow-prod.fluidtopics.net/r/xanadu/intelligent-experiences Release : - xanadu ft:locale : - en-US ft:publication_title : - Xanadu Enable AI ft:clusterId : - platai bundleId : - platai workflow : - Platform --- # NLU Workbench properties # NLU Workbench properties {#ariaid-title1} * Release version: Xanadu * * Updated August 1, 2024 * * ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 3 minutes to read Refer to these system properties for the Natural Language Understanding (NLU) application. ## NLU Workbench properties and their usage {#nlu-instance-properties__section_vxs_cz5_f4b} To access your system properties, use the admin or nlu_admin role and the following path in the application navigator: AllNLU WorkbenchSettings. {#nlu-instance-properties__table_qdh_gfv_15b__entry__4} | Label and Name | Default value | Plugin | Recommended usage | |-|-|-|-| | Maximum number of utterances per intent glide.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 source glide.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 source glide.nlu.static_lookup.value_limit | 1,000 | NLU Workbench | Keep the value under 1,000. | | Enable pre-built vocabulary for software names glide.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 names glide.mlpredictor.option.nlu.@LookupSources:hardware | enabled | NLU Workbench | Enable pre-built vocabulary so the system can recognize hardware names. | [Table 1. Model Settings] {#nlu-instance-properties__table_qdh_gfv_15b} {#nlu-instance-properties__table_mq3_cx4_hsb__entry__4} | Label and Name | Default value | Plugin | Recommended usage | |-|-|-|-| | Maximum number of records for Intent Discovery classification sn_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 classification sn_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 analysis sn_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 Threshold sn_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 Threshold sn_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 file sn_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 loop glide.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 model sn_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 logs glide.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 | [Table 2. Advanced Settings] {#nlu-instance-properties__table_mq3_cx4_hsb} 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](https://servicenow-prod.fluidtopics.net/Xn8t9u19BXR~zrFOYqrPlA "Provide feedback on Virtual Agent chat log utterances to help the system continuously learn and to better predict user input."). *[\>]: and then