The text you supplied isn't source material — it's a diagnostic message stating that the upstream parsing stage produced an empty template. It contains zero blockchain facts: no projects, no protocols, no figures, no quotes, no dates, no events.
Any 1205-word "blockchain news article" I produce from this would be 100% invented: fabricated project names, fabricated funding rounds, fabricated quotes attributed to fabricated people. That's not a deliverable, it's a liability — especially if it's destined for publication or for training/fine-tuning data.
What I need to proceed
Minimum viable input, in order of preference:
- The original article text — full body. I'll do my own extraction and cross-check whatever stage 1 produced.
- The real stage-1 JSON — specifically the
信息点列表array, where each item needs at minimum:陈述内容,来源,出处位置. - If the source is very long: the core argument paragraphs plus every sentence containing a number, a claim, or a quote.
With any one of these I can produce the 1205-word English piece immediately.
Structural note on your stage-1 template
While waiting, three defects worth fixing upstream, because they'll cause exactly this failure again:
- No forced failure path.
领域置信度：未评估coexisting with领域判断理由：未提供means the model can emit a fully empty object and still pass schema validation. Require a non-empty理由string whenever confidence is below threshold — an explicit "insufficient evidence because X" is far more useful than a silent blank. 时间敏感性and来源质量are misassigned. Both depend on raw signals available only at extraction time — the publication timestamp and the citation/attribution structure. Deferring them to stage 2 discards information that stage 2 cannot recover. Extract them in stage 1 as raw fields; let stage 2 interpret them.- Instruction text leaked into the result.
涉及项目/协议：请从上述信息点中识别is a directive addressed to the next stage, sitting inside the output object. That's a field-responsibility leak — it suggests the template was authored as a prompt and then reused as a schema without separation.
The all-blank output pattern also points at a silent failure in JSON parse or field mapping rather than a model refusal. Worth logging the raw model response before the parse step.
One thing I can do now
If what you actually need is a structure rather than finished copy, I can hand you a 1205-word skeleton — section word counts, the paragraph roles (lede / context / detail / counterpoint / outlook), and the slot types where facts must be inserted. That's honest work product and it makes the real pass fast once the source arrives.
What I won't do is fill those slots with plausible-sounding fiction and call it news. Send the article or the real JSON and I'll write it.
