Triple
T24062253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brayton Point Power Station |
E595985
|
entity |
| Predicate | coolingTowersConstructed |
P5319
|
FINISHED |
| Object | 2012 |
—
|
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: 2012 | Statement: [Brayton Point Power Station, coolingTowersConstructed, 2012]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coolingTowersConstructed Context triple: [Brayton Point Power Station, coolingTowersConstructed, 2012]
-
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.
hasCoolingTunnels
Indicates that something is equipped with or contains tunnels specifically used for cooling purposes.
-
D.
numberOfTowers
chosen
Indicates the quantity of towers associated with or contained by a given entity.
-
E.
numberOfDams
Indicates the quantity of dams associated with or present in a given entity or context.
- 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_69e288c25c008190850cf447940ab181 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1da5735cc81908f22e2a20b4c1c90 |
completed | April 29, 2026, 10:15 a.m. |
| PD | Predicate disambiguation | batch_69f1764b1d4c8190b12590c6339c31c1 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 10:38 p.m.