Triple
T22997090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abell 3571 |
E572529
|
entity |
| Predicate | hasHotGasTemperature |
P4459
|
FINISHED |
| Object | on the order of several keV |
—
|
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: on the order of several keV | Statement: [Abell 3571, hasHotGasTemperature, on the order of several keV]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHotGasTemperature Context triple: [Abell 3571, hasHotGasTemperature, on the order of several keV]
-
A.
containsHotGas
Indicates that one entity encloses or holds within it a quantity or region of hot gas.
-
B.
hasTemperature
chosen
Indicates that an entity possesses or is characterized by a specific temperature value.
-
C.
exhaustGasTemperature
Indicates the temperature of the exhaust gases produced by an engine or combustion process.
-
D.
isHot
Indicates that an entity has a high temperature or is perceived as very warm.
-
E.
hasColdGas
Indicates that an entity possesses or contains cold gas, typically referring to gas at relatively low temperatures in an astrophysical or physical 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_69e245b6a3ac81908087599eefe3e365 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182f452b48190951fc5dde56c1bb2 |
completed | April 29, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_69ef3b974e7c8190b8be11dbb4518693 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:50 p.m.