Triple
T32126971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salem Unit 2 |
E820526
|
entity |
| Predicate | usesCoolingWaterIntake |
P68556
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Salem Unit 2, usesCoolingWaterIntake, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesCoolingWaterIntake Context triple: [Salem Unit 2, usesCoolingWaterIntake, yes]
-
A.
hasThermalWaterUse
Indicates that something makes use of thermal water, typically for purposes such as heating, bathing, energy production, or therapeutic applications.
-
B.
usesWaterStorage
Indicates that an entity relies on or incorporates stored water as part of its operation, function, or process.
-
C.
coolingRequirement
Indicates that an entity requires or is subject to a specific amount or type of cooling to operate within acceptable conditions.
-
D.
hasCoolingSource
Indicates that one entity provides or serves as a cooling source for another entity.
-
E.
hasWaterUse
chosen
Indicates a relationship where one entity utilizes or consumes water for a particular purpose, process, or function.
- 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_69f34902d42c819083a8e6bba9a8bb9a |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd32848ea88190a71e6df402bbb30e |
completed | May 8, 2026, 12:47 a.m. |
| PD | Predicate disambiguation | batch_69fd2d7e95588190991d5f21e25155df |
completed | May 8, 2026, 12:25 a.m. |
Created at: May 1, 2026, 12:29 a.m.