Triple
T16123691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arnhem–Nijmegen metropolitan area |
E391208
|
entity |
| Predicate | isEconomicRegion |
P1027
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Arnhem–Nijmegen metropolitan area, isEconomicRegion, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isEconomicRegion Context triple: [Arnhem–Nijmegen metropolitan area, isEconomicRegion, true]
-
A.
isMajorEconomicAreaFor
Indicates that a location or region serves as a primary center of significant economic activity for a specified entity or sector.
-
B.
servesEconomicRegion
Indicates that an entity provides services, support, or functions that benefit or are directed toward a particular economic region.
-
C.
isInEconomicZone
Indicates that one entity lies within the designated economic jurisdiction or exclusive economic zone of another entity.
-
D.
hasMajorEconomicRegion
chosen
Indicates that an entity includes, is associated with, or is part of a primary or significant economic region within a larger economic or geographic context.
-
E.
isRegion
Indicates that one entity functions as a geographic or administrative region associated with another entity.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2020342988190add65c784b8ee179 |
completed | April 17, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69e1828518c48190a8ef3aaa46a1f639 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5 a.m.