Triple
T1814210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Didcot |
E40398
|
entity |
| Predicate | powerStationType |
P21222
|
FINISHED |
| Object | coal-fired (Didcot A) |
—
|
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: coal-fired (Didcot A) | Statement: [Didcot, powerStationType, coal-fired (Didcot A)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: powerStationType Context triple: [Didcot, powerStationType, coal-fired (Didcot A)]
-
A.
powerplantType
chosen
Indicates the specific kind or category of power plant associated with an entity, based on how it generates energy.
-
B.
powerplantFor
Indicates that one entity functions as the power plant or primary energy source serving another entity.
-
C.
energyType
Indicates the kind or category of energy associated with an entity or process.
-
D.
powerplant
Indicates that an entity functions as a facility or installation where energy sources are converted into usable power, typically electricity.
-
E.
powerplantRole
Indicates that one entity serves in a specific functional or operational role relative to a power plant.
- 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_69a8864526c081908a3a4d74f689e2c5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aba67721788190951beae25e885457 |
completed | March 7, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69aa61d884548190a19cf3a6b5ae9d48 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:32 p.m.