Triple
T9144087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Desert Hot Springs wind farms |
E219403
|
entity |
| Predicate | typicalTurbineType |
P87014
|
FINISHED |
| Object | horizontal-axis wind turbine |
—
|
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: horizontal-axis wind turbine | Statement: [Desert Hot Springs wind farms, typicalTurbineType, horizontal-axis wind turbine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTurbineType Context triple: [Desert Hot Springs wind farms, typicalTurbineType, horizontal-axis wind turbine]
-
A.
turbineType
Indicates the specific kind or category of turbine associated with or used by an entity.
-
B.
turbineCapacity
Indicates the power-generating capacity or rated output of a turbine.
-
C.
hasTurbines
Indicates that one entity is equipped with, contains, or includes one or more turbines in relation to another entity.
-
D.
powerplantType
Indicates the specific kind or category of power plant associated with an entity, based on how it generates energy.
-
E.
typicalShaftType
Indicates the usual or characteristic type of shaft associated with an entity or configuration.
- F. None of above. chosen
Provenance (4 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_69ca83e121dc81909912bd66953081c5 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca91548248190ae0b63edebf3d674 |
completed | April 1, 2026, 5:11 a.m. |
| PD | Predicate disambiguation | batch_69cc6603ce8c8190bf6e8d6754bdec54 |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc6a3d230881909635b2ccea35cedb |
completed | April 1, 2026, 12:43 a.m. |
Created at: March 30, 2026, 7:19 p.m.