Triple
T5791116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edict of Fontainebleau |
E128394
|
entity |
| Predicate | impactOnMigration |
P4275
|
FINISHED |
| Object | emigration of Huguenots to the Dutch Republic |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: emigration of Huguenots to the Dutch Republic | Statement: [Edict of Fontainebleau, impactOnMigration, emigration of Huguenots to the Dutch Republic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnMigration Context triple: [Edict of Fontainebleau, impactOnMigration, emigration of Huguenots to the Dutch Republic]
-
A.
impactIfCompleted
Indicates the effect or consequence that will occur if the referenced task or action is fully completed.
-
B.
migration
chosen
Indicates the movement of entities from one location or context to another, often across boundaries or over time.
-
C.
impactOnBusiness
Indicates the effect or influence that one factor, event, or action has on a business’s performance, operations, or outcomes.
-
D.
encodingImpact
Indicates how one encoding or encoding choice affects, modifies, or constrains another process, representation, or outcome.
-
E.
migrationCause
Indicates the reason or driving factor that leads an entity to migrate from one place to another.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c00845ca68819081a2ce3ecca577f7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02a56c73c81908a1c72c86e474b54 |
completed | March 22, 2026, 5:43 p.m. |
| PD | Predicate disambiguation | batch_69c021d2cd608190b98a7e3aa7001d27 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:51 p.m.