Triple
T28286617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kalinin-3 |
E713297
|
entity |
| Predicate | coolingWaterSource |
P54649
|
FINISHED |
| Object | nearby water bodies in Tver Oblast |
—
|
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: nearby water bodies in Tver Oblast | Statement: [Kalinin-3, coolingWaterSource, nearby water bodies in Tver Oblast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coolingWaterSource Context triple: [Kalinin-3, coolingWaterSource, nearby water bodies in Tver Oblast]
-
A.
coolingWaterSourceLicensed
Indicates that the source of cooling water used (e.g., for industrial or energy production purposes) is formally licensed or authorized by the relevant regulatory authority.
-
B.
hasCoolingSource
chosen
Indicates that one entity provides or serves as a cooling source for another entity.
-
C.
sourceOfWaterSupply
Indicates that one entity serves as the origin or provider of another entity’s water supply.
-
D.
waterTemperatureAtSource
Indicates the temperature of water measured at its point of origin or source location.
-
E.
waterType
Indicates the specific kind or category of water associated with an entity (e.g., fresh, salt, brackish).
- 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_69efb52371d88190a1381c4e58a3b731 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f6448075c48190a28340ceb79c7d3e |
completed | May 2, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 11:26 p.m.