What this category of data looks like
Thermal coal research report sources mainly include coal industry research institutions, spot data reports released by domestic coastal ports, futures exchange research reports, and internal analysis documents from large coal production and trading enterprises. Updates follow a monthly regular report rhythm, with temporary reports released when policies change or port inventory fluctuates. Most documents are in PDF format, containing structured data tables, price trend charts, and written analysis. Core fields cover thermal coal calorific value (usually measured in kcal/kg), flat price (yuan/ton), port inventory (ten thousand tons), railway shipment volume (ten thousand tons), downstream thermal power generation (hundred million kWh), and some reports include segmented regional supply and demand data.
What constraints do these characteristics impose on the knowledge base retrieval and recall link?
Dispersed sources lead to inconsistent document formats and field naming across different institutions. For example, some reports use "spot price" instead of "flat price", which increases the difficulty of semantic matching. Unstructured charts and long text structures cause standard chunking logic to lose associations between data and context. Uncertain update frequency requires flexible knowledge base synchronization mechanisms to avoid delayed coverage of the latest policy and price data. Unit differences in professional fields require semantic matching during retrieval; literal keyword matching alone will cause matching errors for core data such as calorific value and price.
How to set the configuration
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Chunk Length | 800–1200 characters | Each segment of a thermal coal research report must contain complete supply and demand logic or professional data, to avoid truncating associated descriptions of key fields such as calorific value and price |
Chunk Overlap Ratio | 10%–15% | Core data such as prices and inventory in thermal coal research reports often appear across segments. Overlapping settings preserve context associations and reduce semantic fragmentation |
Recall Similarity Threshold | 0.72–0.80 | Thermal coal research reports are dense with professional terminology. A threshold that is too low will introduce irrelevant industry reports, while a threshold that is too high will miss precisely matched segmented data |
Maximum Single Recall Entries | Top 6–8 entries | Thermal coal research reports have high information density. Too many recalled entries will exceed maxContext limits, leading to truncation of key information |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Single thermal coal research reports often contain a large number of charts and long text, with long parsing time. The timeout threshold must be extended to avoid parsing failures |
Re-rank Return Count | Top 3–4 entries | Prioritize returning the most matching report segments, to avoid redundant information interfering with final question answering results |
The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material format, data volume and business rules. Specific issues require targeted analysis, and it is recommended to test on your own samples before finalizing settings.
Three common errors
- Phenomenon: After uploading a single thermal coal research report PDF, search results often display irrelevant content or missing key data. Cause:
Chunk LengthandChunk Overlap Ratioare not adjusted for the long text and professional fields of thermal coal research reports, leading to truncated key data or semantic fragmentation in chunks. - Phenomenon: In FastGPT 4.6.7, when
Chunk Lengthis set to 5000 tokens andmaxContextis set to 1500 tokens, search results still exceed quota limits. Cause: The matching relationship betweenmaxContextandChunk Lengthis not considered. After large chunking, the total final recalled context is not restricted, causing content exceeding window limits to be forcibly truncated or omitted. - Phenomenon: When searching for thermal coal-related keywords, a large number of research reports for other coal categories are returned. Cause: Reasonable
Recall Similarity ThresholdandMaximum Single Recall Entriesare not set, leading to low-matching non-target category research reports being included in the recall range.
How to confirm proper configuration
- Upload a single standard thermal coal research report PDF, view the parsed chunk list in the knowledge base, and confirm each chunk contains complete professional data and logical statements.
- Enter specific thermal coal professional keywords, such as "5500 kcal/kg thermal coal flat price", and check if the retrieved chunk segments contain matching fields and units.
- Adjust the
Recall Similarity Threshold, compare changes in search result relevance, and confirm the threshold meets the matching accuracy requirements of the current business. - View the knowledge base parsing logs to confirm that parsing of single thermal coal research reports does not trigger timeout errors.
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.