Triple
T8638119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Didcot Power Station |
E204572
|
entity |
| Predicate | numberOfCoolingTowers |
P5319
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Didcot Power Station, numberOfCoolingTowers, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCoolingTowers Context triple: [Didcot Power Station, numberOfCoolingTowers, 6]
-
A.
hasCoolingTowers
Indicates that an entity possesses or is equipped with one or more cooling towers as part of its infrastructure or system.
-
B.
hasCoolingTowerType
Indicates that an entity is associated with, or equipped with, a specific type or category of cooling tower.
-
C.
numberOfTowers
chosen
Indicates the quantity of towers associated with or contained by a given entity.
-
D.
coolingRequirement
Indicates that an entity requires or is subject to a specific amount or type of cooling to operate within acceptable conditions.
-
E.
numberOfTurbines
Indicates the quantity of turbines associated with a given entity or installation.
- 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_69ca834b903c8190add96cc651e1a477 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc47944d1c819081f448f14d04bf9d |
completed | March 31, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69cc455d6d448190a2da2a319ac78c37 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:28 p.m.