What This Category of Data Looks Like
Telecommunications service research report data comes from securities firm telecommunications industry research teams, public telecommunications industry association reports, operator operational monthly reports, and technical white papers from telecommunications equipment manufacturers. Update frequency aligns with core industry events. New reports are added after major technology iterations or policy releases. The standard update cycle runs from monthly to quarterly. Document structures include report summaries, overall industry landscape, segmented track analysis, core enterprise operating data, and policy interpretations. Fields include publishing institution, release date, covered telecommunications sub-sectors, core viewpoints, and quantitative supporting data. Common units for quantitative data include hundreds of millions of yuan, ten thousand units, ten thousand households, and similar metrics.
Constraints on Knowledge Base Retrieval and Recall
The scattered sources and non-standard formats of telecommunications service research reports require the knowledge base parsing module to support multi-format adaptation and custom field extraction. This prevents core information loss from format differences. The non-fixed update schedule requires configuring an incremental synchronization mechanism. Only newly added or modified reports are indexed to update, reducing computing overhead. The large number of sub-sectors and quantitative data fields requires setting weight priorities for track keywords and data fields during retrieval. This avoids recalling irrelevant sub-sector reports. The relatively long length of individual research reports requires a segmentation strategy optimized for long-text splitting. This prevents overflow of the large model context window.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Telecommunications service research reports contain long paragraphs of industry analysis and data tables. This length balances context completeness and retrieval accuracy |
recall_top_k | Top 8–12 results | There are many segmented tracks in telecommunications service research reports. Sufficient candidate results must be recalled to cover relevant content across different sub-sectors |
similarity_threshold | 0.72–0.85 | Research report content is highly professional. This threshold filters low-similarity irrelevant results while retaining precisely matched content from sub-sectors |
incremental_update | Enabled | Updates to telecommunications industry research reports have no fixed cycle. Incremental updates reduce duplicate indexing calculations and improve update efficiency |
parse_field_mapping | Map to "publishing institution, release date, sub-sector, core data" | Core retrieval needs for telecommunications service research reports focus on sub-sectors and data support. Field mapping improves the accuracy of field-level recall |
rerank_top_k | Top 3–5 results | The re-ranking step needs to filter the most relevant report snippets. This avoids redundant content entering the large model context |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Phenomenon: After configuring both a knowledge base retrieval and tool calling module in a workflow, the AI does not return knowledge base report content, and only calls external tools. Cause: Retrieval weight priorities were not adjusted, causing the tool calling trigger condition to take precedence over knowledge base retrieval.
- Phenomenon: After uploading a telecommunications service research report table dataset, some quantitative data fields are not included, resulting in incomplete knowledge base content. Cause: Custom field mapping for
parse_field_mappingwas not set. The default parsing logic does not cover the professional data fields in the research reports. - Phenomenon: Retrieved research report results are too long, exceeding the large model context window limit. Cause:
chunk_sizewas set too large. Long research reports were not properly segmented, causing single segment content to exceed the context carrying range.
How to Confirm Proper Configuration
- Upload a standard telecommunications service research report, check the parsed segmented content, confirm that core fields and quantitative data are correctly extracted.
- Initiate a query targeting telecommunications service sub-sectors, verify that the number of retrieved results and similarity meet configuration expectations.
- Configure a workflow to link the knowledge base and tool calling modules, execute a test query, confirm that the AI can prioritize returning knowledge base research report content.
- Initiate an incremental update task, check the indexing logs, confirm that only newly added or modified research reports are re-indexed.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.