Triple
T4619116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaus Media |
E100935
|
entity |
| Predicate | hasEffectiveTemperature |
P57025
|
FINISHED |
| Object | approximately 4300 K |
—
|
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: approximately 4300 K | Statement: [Kaus Media, hasEffectiveTemperature, approximately 4300 K]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEffectiveTemperature Context triple: [Kaus Media, hasEffectiveTemperature, approximately 4300 K]
-
A.
hasTemperature
Indicates that an entity possesses or is characterized by a specific temperature value.
-
B.
equilibriumTemperature
Indicates the temperature at which a system’s heat exchange balances so that no net change in its thermal state occurs.
-
C.
hasAverageSurfaceTemperature
Indicates that an entity is associated with a specific mean value of its surface temperature over a defined period or condition.
-
D.
maxSurfaceTemperature
Indicates the highest temperature that the surface of an entity can reach or sustain under specified conditions.
-
E.
surfaceTemperature_K
Indicates the temperature of a surface expressed in kelvins.
- 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_69bd43cf363c819087fd5ab441b4a3f4 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd59e3e6948190925e2cfad20dcc8c |
completed | March 20, 2026, 2:29 p.m. |
| PD | Predicate disambiguation | batch_69bd522fd5c48190ad2bffc0a5bc9061 |
completed | March 20, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69bd556b93cc8190ab817d2817109a0b |
completed | March 20, 2026, 2:10 p.m. |
Created at: March 20, 2026, 1:12 p.m.