Triple
T26984059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cavrois family |
E679683
|
entity |
| Predicate | industryRegion |
P15910
|
FINISHED |
| Object | Nord-Pas-de-Calais |
—
|
NE NERFINISHED |
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: Nord-Pas-de-Calais | Statement: [Cavrois family, industryRegion, Nord-Pas-de-Calais]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: industryRegion Context triple: [Cavrois family, industryRegion, Nord-Pas-de-Calais]
-
A.
developmentRegion
Indicates the geographic or administrative region in which something is developed, produced, or primarily created.
-
B.
marketRegion
Indicates the geographic or demographic area in which a product, service, or entity is actively marketed or targeted.
-
C.
isIndustrialRegion
chosen
Indicates that a given area functions primarily as a center of industrial activity, characterized by significant manufacturing, production, or related industrial operations.
-
D.
hasHeadquartersInRegion
Indicates that an organization’s main administrative or corporate headquarters is located within a specified geographic region.
-
E.
regionalEconomyType
Indicates the type or classification of an economy associated with a specific region.
- 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_69eeeb5138ac8190b3c273ddc659a54f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651a931748190a637e631a52bbfaa |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 27, 2026, 6:47 a.m.