Triple
T31424202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sweden and Denmark |
E801614
|
entity |
| Predicate | hasJointMetropolitanRegion |
P144875
|
FINISHED |
| Object | Øresund Region |
—
|
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: Øresund Region | Statement: [Sweden and Denmark, hasJointMetropolitanRegion, Øresund Region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasJointMetropolitanRegion Context triple: [Sweden and Denmark, hasJointMetropolitanRegion, Øresund Region]
-
A.
belongsToMetropolitanRegion
Indicates that one geographic or administrative area is part of, or included within, a larger metropolitan region.
-
B.
isBinationalUrbanArea
chosen
Indicates that an urban area spans across and functionally integrates cities or communities in two different nations.
-
C.
metropolitanAreaWith
Indicates that one entity is a metropolitan area that includes, is associated with, or encompasses the other entity.
-
D.
hasMetropolitanAreaType
Indicates that an entity is associated with a specific type or classification of metropolitan area (e.g., urban, suburban, metropolitan region category).
-
E.
hasCapitalRegionRelation
Indicates a relationship where one entity serves as the capital region or administrative capital area of 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_69f348c26f048190b4adadd71b4596c5 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a5f71b2c8190aade8a83f465be0c |
completed | May 3, 2026, 1:33 a.m. |
| PD | Predicate disambiguation | batch_69f69fe66df08190958558d63ee623d9 |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 30, 2026, 8:51 p.m.