--- sourceDocument: Zurich Enable AI sourceDocumentLink: https://www.servicenow.com/docs/r/zurich/intelligent-experiences Release : - zurich ft:locale : - en-US ft:publication_title : - Zurich Enable AI ft:clusterId : - platai bundleId : - platai workflow : - Platform --- # NLU Workbench properties # NLU Workbench properties {#ariaid-title1} Release version: Zurich Updated July 31, 2025 ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 3 minutes to read Summarize ![AI sparkle icon](https://servicenow.com/docs/portal-asset/ai-sparkle-icon) Summarized using AI This content was generated using new OpenAI-powered functionality. Results are provided on an as is basis and are not guaranteed to be accurate or complete. ## Summary of NLU Workbench properties The NLU Workbench properties define configurable system settings for managing and optimizing the Natural Language Understanding (NLU) application within ServiceNow. These properties control limits, enable features, and impact model training and performance. Access to these settings requires theadminornluadminroles via the path:All \> NLU Workbench \> Settings. Show full answer Show less ## Model Settings * **Utterances per intent:** Limit to fewer than 200 utterances to maintain balanced intent sizes; allowed range is 6 to 300. * **Vocabulary source limits:** Maximum 100,000 records for Table vocabulary sources and 1,000 values for List vocabulary sources to ensure manageable data volume. * **Pre-built vocabularies:** Enable recognition of software and hardware names to improve model understanding by activating corresponding properties. ## Advanced Settings * **Intent Discovery record limits:** Use between 10,000 and 500,000 records to achieve high-quality classification results. * **Performance analysis data:** At least 5,000 records are recommended for effective NLU performance evaluation. * **Conflict detection thresholds:** Set moderate threshold below critical threshold, both as decimals between 0 and 1 (defaults: 0.85 and 0.95). * **Batch test import:** Limit import files to 10,000 rows to ensure system stability during testing. * **Expert Feedback Loop:** Display up to 300 utterances from Virtual Agent chat logs for review; require feedback on at least 100 utterances before tuning models. * **Chat log data fetch limits:** Default fetch limit is 3,000 records; can be increased up to 50,000 for high NLU usage to provide more feedback data. * **Data pruning size limits:** Label Candidate and Labeled Data tables are recommended to be limited to 10,000 records each for efficient pruning. * **Scheduled model training:** Option to enable off-peak NLU model training to avoid service disruption; default is disabled. ## Practical Implications for ServiceNow Customers By correctly configuring these properties, customers can optimize NLU model quality, maintain system performance, and enhance training and feedback workflows. Adhering to recommended limits prevents performance degradation and data overload. Enabling pre-built vocabularies improves recognition of common software and hardware terms. Using the Expert Feedback Loop efficiently requires setting appropriate feedback volume parameters and managing data fetch sizes. Scheduling model training during off-peak hours helps minimize impact on instance availability. 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://www.servicenow.com/docs/P_AI69lUEfo13cz_pA~o6g "Provide feedback on Virtual Agent chat log utterances to help the system continuously learn and to better predict user input."). *[\>]: and then