Triple
T3798486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bahrain World Trade Center |
E91630
|
entity |
| Predicate | windTurbineDiameter |
P22940
|
FINISHED |
| Object | approximately 29 metres |
—
|
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: approximately 29 metres | Statement: [Bahrain World Trade Center, windTurbineDiameter, approximately 29 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: windTurbineDiameter Context triple: [Bahrain World Trade Center, windTurbineDiameter, approximately 29 metres]
-
A.
rotorDiameter
chosen
Indicates the relationship where a rotor is associated with a specific measurement representing the diameter of its circular span.
-
B.
turbineCapacity
Indicates the power-generating capacity or rated output of a turbine.
-
C.
numberOfTurbines
Indicates the quantity of turbines associated with a given entity or installation.
-
D.
hasTurbines
Indicates that one entity is equipped with, contains, or includes one or more turbines in relation to another entity.
-
E.
turbineType
Indicates the specific kind or category of turbine associated with or used by an 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_69aed96354f48190a768966d6bd19b04 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee8db8a288190afd1e3b9dcf02e97 |
completed | March 9, 2026, 3:35 p.m. |
| PD | Predicate disambiguation | batch_69aee7461abc8190945716f4b93e1a18 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:15 p.m.