Triple
T6697766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Centaurus Cluster |
E152793
|
entity |
| Predicate | hasCoolingFlow |
P72502
|
FINISHED |
| Object | yes, in central regions |
—
|
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, in central regions | Statement: [Centaurus Cluster, hasCoolingFlow, yes, in central regions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoolingFlow Context triple: [Centaurus Cluster, hasCoolingFlow, yes, in central regions]
-
A.
hasCoolingSource
Indicates that one entity provides or serves as a cooling source for another entity.
-
B.
coolingRequirement
Indicates that an entity requires or is subject to a specific amount or type of cooling to operate within acceptable conditions.
-
C.
coolingMethod
Indicates the technique or process used to remove heat from something or keep it at a lower temperature.
-
D.
hasCoolingTowerType
Indicates that an entity is associated with, or equipped with, a specific type or category of cooling tower.
-
E.
coolingStrategy
Indicates the method or approach used to reduce or control temperature in a system or environment.
- F. None of above. chosen
Provenance (4 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_69c68807adbc8190b8632df42b39eda0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d16897e48190b43eda2206b14d6a |
completed | March 27, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69c6d089c7488190a00853fb12f53b2a |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d1668a7c8190ae93951f9ba2df10 |
completed | March 27, 2026, 6:50 p.m. |
Created at: March 27, 2026, 2:05 p.m.