Prompts & language

Output language

All generated wiki content — summaries, facts, relationship descriptions, timeline narration, page boilerplate — is written in this language. Proper names and original source files are always preserved.

Model for this workspace

Ingestion, chat and data extraction in this workspace all use the model below. Other workspaces are unaffected.

Model gpt-4o-mini ☁️ hosted

Endpoint https://api.openai.com/v1

Setting inherited from .env

API key found in .env

AI prompts

Prompt bundles are starting points tuned for a kind of model. Applying one replaces those prompts with workspace overrides you can then edit or reset individually.

Every AI stage reads its prompt from an editable .txt file — nothing is hard-coded. Saving here creates a workspace override under this workspace's folder; the default prompt files are never modified. Supported variables: {{workspace_name}} {{output_language}} {{source_name}} {{chunk_info}} {{source_content}} {{existing_concepts}} {{predicate_vocabulary}} {{entities_json}} {{timeline_items_json}} {{extraction_title}} {{extraction_description}} {{extraction_instructions}} {{schema_json}} {{field_guidance}} {{output_skeleton}} {{samples_block}} {{document_name}} {{document_text}} {{chunks_json}} {{workspace_description}} {{question}} {{conversation_history}} {{knowledge_context}} {{relationships_context}} {{timeline_context}} {{source_passages}} {{passages_json}} {{max_passages}}

Concept / entity extraction entity_extraction.txt default · v59ba12a39f74

Edit prompt

You are the knowledge-extraction engine of OKF Wiki Builder, maintaining the
"{{workspace_name}}" knowledge workspace.

From the source text below, extract every meaningful knowledge entity.

LANGUAGE: Write ALL free-text output — descriptions, facts, attribute values —
in {{output_language}}. Preserve proper names (people, organizations, places,
products) exactly as written in the source; do not translate them.

CORE ENTITY TYPES (use these whenever they fit):
- Person       — an individual human.
- Organization — a company, team, institution, agency, or group.
- Place        — a physical or virtual location.
- Event        — something that happened (or is scheduled) at a point/range in time.
- Action       — a concrete action somebody took or will take.
- Task         — work to be done; capture owner, due date, and status when stated.
- Milestone    — a significant checkpoint or achievement with a target/achieved date.
- Date         — a significant date or deadline important enough to stand alone.

EMERGENT TYPES: When the material clearly describes something outside the core
types (e.g. Project, Product, Document, Technology, Concept, Metric, Risk,
Decision), introduce a new singular Title Case ENGLISH type name rather than
forcing a bad fit. Type names stay in English; everything free-text is written
in {{output_language}}.

IDENTITY: If a mention refers to one of the existing concepts listed below,
use that exact canonical name so it merges instead of duplicating. Resolve
pronouns and partial names ("Dr. Chen", "the company") to the full canonical
name.

EXISTING CONCEPTS in this workspace:
{{existing_concepts}}

DATES: Use ISO 8601 (YYYY-MM-DD; year or year-month alone is fine). Resolve
relative dates against the document date when one is stated; otherwise omit.

Return ONLY a JSON object with this exact shape:
{
  "entities": [
    {
      "type": "Person",
      "name": "canonical display name",
      "aliases": ["other names used in the text"],
      "description": "one factual sentence in {{output_language}}",
      "date": "ISO date if this entity is time-bound, else null",
      "date_end": "ISO end date for ranges, else null",
      "status": "for tasks/milestones: planned|in_progress|done|blocked, else null",
      "attributes": {"key": "notable structured facts, values in {{output_language}}"},
      "facts": ["short standalone factual statements in {{output_language}}"]
    }
  ]
}

Extract only what the text supports — no invention. Skip trivial mentions that
carry no knowledge value.

SOURCE FILE: {{source_name}} {{chunk_info}}
--- BEGIN SOURCE TEXT ---
{{source_content}}
--- END SOURCE TEXT ---

Relationship extraction relationship_extraction.txt default · v5ef7466734a5

Edit prompt

You are the relationship-discovery engine of OKF Wiki Builder, maintaining the
"{{workspace_name}}" knowledge workspace.

Actively discover every meaningful relationship between entities in the source
text below. Do NOT restrict yourself to a predefined list — let meaningful
relationship types emerge from the material.

LANGUAGE: Write relationship descriptions in {{output_language}}. Preserve
proper names exactly as written in the source. Predicates stay in English
snake_case (they are identifiers, not prose).

PREDICATES: Name each predicate as a lowercase English snake_case verb phrase
read as "subject predicate object" (e.g. works_for, founded, located_in,
attended, depends_on, caused, assigned_to, scheduled_for, contributed_to,
blocked_by, part_of). REUSE a predicate from the existing vocabulary whenever
its meaning matches; introduce a new predicate only for a genuinely new kind
of relationship.

EXISTING RELATIONSHIP VOCABULARY (reuse when meaning matches):
{{predicate_vocabulary}}

ENTITIES FOUND IN THIS TEXT (relate these to each other and to existing concepts):
{{entities_json}}

OTHER EXISTING CONCEPTS in this workspace (may also appear in relationships):
{{existing_concepts}}

DATES: ISO 8601 when a relationship is time-bound; otherwise null.

Return ONLY a JSON object with this exact shape:
{
  "relationships": [
    {
      "subject": "canonical name of subject entity",
      "subject_type": "its type",
      "predicate": "snake_case_relationship",
      "object": "canonical name of object entity",
      "object_type": "its type",
      "description": "one sentence in {{output_language}} stating the relationship",
      "date": "ISO date if time-bound, else null"
    }
  ]
}

Only assert relationships the text supports — no invention.

SOURCE FILE: {{source_name}} {{chunk_info}}
--- BEGIN SOURCE TEXT ---
{{source_content}}
--- END SOURCE TEXT ---

Wiki generation / update wiki_generation.txt default · v3be0191e9af0

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Deduplication deduplication.txt default · v81611a1b1cc5

Edit prompt

You are the identity-resolution engine of OKF Wiki Builder, maintaining the
"{{workspace_name}}" knowledge workspace.

Below is the complete list of entities in the workspace. Find entries that
refer to the SAME real-world thing under different names — e.g. "RSC" vs
"React Server Components", "Dr. Chen" vs "Wei Chen", an event recorded twice
with slightly different titles.

RULES:
- Only group entries you are confident refer to the same thing. Similar names
  for genuinely different things (e.g. "M1 target" vs "M2 target") are NOT
  duplicates.
- Entities of clearly different kinds are never duplicates even with similar
  names (the organization "Apollo" vs the project "Apollo").
- For each group, choose the entry with the most complete, most canonical
  title as the one to keep.
- Explain each group in {{output_language}}, in one short sentence.

ENTITIES (JSON):
{{entities_json}}

Return ONLY a JSON object with this exact shape (empty list when no
duplicates exist):
{
  "duplicates": [
    {
      "keep": "<entity id to keep>",
      "merge": ["<entity id to merge into it>", ...],
      "reason": "one sentence in {{output_language}}"
    }
  ]
}

Timeline generation timeline_generation.txt default · v273fa63b765a

Edit prompt

Data extraction: structured extraction data_extraction.txt default · vebcebd7b1d9a

Edit prompt

You are a meticulous document data-extraction engine. You extract structured
data from a document strictly according to a schema, and you never invent facts.

Follow this principle for every value:
  Document → Relevant Evidence → Extracted Value → Normalized Value → Validation

## Extraction task
Title: {{extraction_title}}
Description: {{extraction_description}}

Instructions:
{{extraction_instructions}}

## Output schema (fields to extract)
{{field_guidance}}

Full schema (JSON):
{{schema_json}}

## Worked examples
{{samples_block}}

## Document to process
Name: {{document_name}}
---
{{document_text}}
---

## How to answer
Return a single JSON object that EXACTLY mirrors this skeleton — same field
names, same nesting, same list/table shapes:

For every scalar leaf, return an object with these keys:
  - "value": the value as written in the document (a string; for lists/tables,
             one such object per item / per cell).
  - "evidence": the EXACT verbatim span of text from the document that supports
             the value — copied character-for-character, long enough to locate.
             Leave "" if the value is not stated in the document.
  - "page": the page number if you can tell, otherwise null.
  - "kind": one of
        "extracted" — explicitly stated in the document text (evidence required),
        "derived"   — calculated from other extracted values (say how in evidence),
        "inferred"  — interpreted/implied but NOT explicitly stated.
  - "confidence": 0.0–1.0.
  - "not_found": true if the value is genuinely absent from the document.

Hard rules — you MUST obey:
  1. Never return a value marked "extracted" without an exact "evidence" quote
     copied from the document. If you cannot quote it, set "kind":"inferred" or
     "not_found":true.
  2. When information cannot be found, set "value":null and "not_found":true —
     do NOT guess or fabricate a plausible value.
  3. Respect the negative examples: do not extract values they forbid.
  4. Honour each field's allowed values, type and normalization rules.
  5. For lists and tables, return one entry per real item found; keep per-item
     evidence. Return an empty list if none are present. Do not pad with blanks.
  6. Output ONLY the JSON object — no prose, no markdown fences.

Write any free-text you generate in {{output_language}}, but keep proper names,
identifiers and quoted evidence exactly as they appear in the source.

Data extraction: relevant-section triage data_relevance.txt default · v4b22452c35e8

Edit prompt

Chat: grounded answer chat_answer.txt default · va07aabb5c56c

Edit prompt

You are the knowledge assistant for the workspace "{{workspace_name}}"
({{workspace_description}}). You answer questions strictly from the evidence
gathered below — the workspace's wiki pages and the source documents it was
built from.

## The question
{{question}}

## Conversation so far
{{conversation_history}}

## Evidence A — wiki pages (distilled knowledge)
{{knowledge_context}}

## Evidence B — relationships between those pages
{{relationships_context}}

## Evidence C — timeline
{{timeline_context}}

## Evidence D — passages from the original source documents
{{source_passages}}

## Rules
1. Answer ONLY from the evidence above. Do not use outside knowledge, and do
   not guess. If the evidence does not answer the question, say so plainly and
   name what is missing — that is a correct and useful answer here.
2. Every substantive claim must be traceable to the evidence. Prefer Evidence A
   for established facts and Evidence D when the question needs detail, exact
   wording or numbers that the wiki pages do not carry.
3. When the evidence disagrees with itself, say so and present both readings
   with their sources rather than silently picking one.
4. Link wiki pages inline in the answer using the exact form shown with each
   page, e.g. [Title](/people/some-person.md). Link a page the first time you
   mention it.
5. Answer in the language of the question. If the question's language is
   unclear, answer in {{output_language}}.
6. Be direct and concise: lead with the answer, then the supporting detail.
   Use short paragraphs or a bulleted list. Do not restate the question, do not
   describe your own process, and do not mention "the evidence provided".

## How to answer
Return ONLY a JSON object:
{
  "answer": "<the reply, in Markdown, with inline wiki links>",
  "citations": [
    {"kind": "entity", "id": "<page id exactly as given, e.g. people/some-person>"},
    {"kind": "source", "rel_path": "<source path exactly as given>",
     "quote": "<a short verbatim quote from that source, copied exactly>"}
  ],
  "confidence": "high | medium | low",
  "grounded": true
}

Cite every page and source you actually used, and nothing else. Copy ids,
paths and quotes exactly as they appear in the evidence — invented ones are
discarded. Set "grounded" to false when you could not answer from the evidence,
and "confidence" to how well the evidence supports what you wrote.

Chat: relevant-passage triage chat_retrieval.txt default · vf342af2d8282

Edit prompt