---
sourceDocument: Brazil Platform Analytics
sourceDocumentLink: https://www.servicenow.com/docs/r/now-intelligence

 Release :

    - brazil

ft:locale :

    - en-US

ft:publication_title :

    - Brazil Platform Analytics

ft:clusterId :

    - par

bundleId :

    - par

workflow :

    - Platform


---

# Logs

# Query Generation logs {#ariaid-title1}

Release version: Brazil  
Updated September 10, 2026  
![](https://www.servicenow.com/docs/portal-asset/ico-clock) 4 minutes to read  
Every call to a Query Generator and its results are logged in the Query Generation Log \[sn_query_gen_log\] table.

## Using the logs {#query-generation-logs__section_using-logs}

Go to Query GenerationAdministrationLogs to inspect failed or incorrect queries.

1. Find the entry by user, date, or utterance.
2. Check Semantic Entities/Dimensions/Segments Count
3. Open Query Constitutor Output to see what was selected.
4. Compare with Semantic Filter Result for raw semantic matches.
{#query-generation-logs__table_troubleshooting__entry__3}

| Symptom | Likely cause | Fix |
|-|-|-|
| "Unable to understand" response | System cannot find a matching table | Improve entity description; rephrase with table name; verify AI search is running; verify that all Indexed Sources are fully processed. |
| Wrong table selected | Similar table names, no disambiguation | Add semantic usage instructions to differentiate. |
| Wrong table selected (permissions) | User lacks read access to the intended table or fields. | Verify and grant table and field read ACLs for the intended data. |
| "Error accessing table data" or "Scope access not granted" response | Some data is in protected application scopes that AI Data Explorer cannot access. | Create ACLs granting access to the scope for AI Data Explorer. Approve the subsequently generated Restricted Caller Access (RCA) records. For more information, see [Enabling access to protected scope applications for AI Data Explorer and Query Generation](https://www.servicenow.com/docs/OSIvck0g675MxcYZ9GHeUQ "AI Data Explorer and Query Generation require additional security configuration to access tables in protected scopes such as Human Resources or Employee Profile scopes."). |
| Missing field in results | Dimension turned off, unclear label, or field not in semantic layer | Check dimension is active; update label. |
| Related fields not pulled in | Referenced table missing from semantic layer or reference dimension turned off | Add and enable the referenced table entity; enable the reference dimension. |
| Wrong filter applied | Bad segment match | Fix segment name and description; disable the segment. |
| No filter when expected | No matching segment; phrasing too vague | Create a manual segment; rephrase question. |
| Segment from report is wrong | Auto-generated segment has stale or irrelevant filter | Disable the report segment source or the specific segment. |
[Table 1. AI Data Explorer troubleshooting guide]

{#query-generation-logs__table_troubleshooting} {#query-generation-logs__table_mqb_hvh_cgc__entry__3}

| Column | Description | Shown by default? |
|-|-|-|
| Created | Timestamp of the call to Query Generation | Yes |
| User | The user from the User \[sys_user\] table who made the call. If this is blank, try Created by. | Yes |
| Utterance | The plain language question asked by the user | Yes |
| Status | The success or otherwise of the call | Yes |
| Error message | If the status is "error," this is the error message that is returned to the user. | Yes |
| Total time | Time in milliseconds it took for the AI to process the query and return the response | Yes |
| "X" time | Time in milliseconds each component X spent processing the query | Yes |
| Semantic Filter Results | Fields in the semantic layer tables that the query references, in JSON | Yes |
| Utterance Bank Results | Questions similar to the user's question (Utterance) that were found in the Utterance Bank and used to interpret the user's question, in JSON | Yes |
| Response | The JSON response to the query | Yes |
| Entities | The records in the Entities table that are referenced by the query. Each record corresponds to a facts table. | Yes |
| Query Constitutor Output | JSON of the query that is generated | Yes |
| Source | The application from which the question was asked. If the question was asked from the ServiceNow Otto panel when it was open in a page that is not part of an application, the UUID of that page is shown instead. | Yes |
| Response | The response that the LLM returns | Yes |
| Generative AI Log | The LLM used for the query | Yes |
| Conversation | Unique chat conversation ID, such as in a ServiceNow Otto Panel to Query Generation conversation | Yes |
| ACL Time | Time it took to validate the Access or Security of the user for the underlying table | No |
| Additional info | Start time, total calls, and other metadata about the AI Search run | No |
| Created by | Person who created the query. Includes ServiceNow® staff members logged on as maint. | No |
| Domain | Domain in which the query was created | No |
| Dot walked | Whether the query included dot walking between tables (true/false) | No |
| Entity has usage score | Whether the entity has a usage score (true/false) | No |
| Entity source | Whether the Source was in ENTITIES, USER SENSE, or SEGMENTS | No |
| Error code | The error code, if there was an error | No |
| Follow Up Generated | The number of follow-up questions that the LLM generated in response to the query | No |
| Follow Up Returned | How many of the generated follow-up questions are actually returned. The questions must refer to tables that the querying user can access and are in the semantic layer, for example. | No |
| LLM Time | Time spent by the large language model (LLM) on the query | No |
| Query Constructor Time | Time spent by the query constructor on the query | No |
| RAG time | Time spent by the retrieval-augmented generation (RAG) on the query | No |
| Semantic Dimensions count | Number of table records (dimensions) examined for the query | No |
| Semantic Entities Count | Number of tables (entities) examined for the query | No |
| Semantic Filter Results | Results of running the semantic filter | No |
| Semantic Filter Time | Time spent by the semantic filter | No |
| Semantic Segments Count | Number of segments examined for the query | No |
| Source Table | Name of table corresponding to Source Id | No |
| Tags | Any tags that you add to the log | No |
| Updated | Date stamp when log entry was last updated | No |
| Updated by | User responsible for last log entry update | No |
| Updates | Count of updates to the log entry | No |
| Utterance bank results | Similar examples extracted from utterance bank | No |
| Utterance bank time | Amount of time spent searching the utterance bank | No |
[Table 2. Query Generation log columns]

{#query-generation-logs__table_mqb_hvh_cgc}
**Related concepts**   

* [Common AI Data Explorer issues and fixes](https://www.servicenow.com/docs/Fp4R7QhG6H1NOmpUB8qdQA "Use Query Generation logs to inspect failed or incorrect queries and identify common issues with AI Data Explorer responses.")

*[\>]: and then