Triple
T2962723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orcus |
E80084
|
entity |
| Predicate | hasMeanSurfaceTemperature |
P2033
|
FINISHED |
| Object | around 40–50 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: around 40–50 K | Statement: [Orcus, hasMeanSurfaceTemperature, around 40–50 K]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeanSurfaceTemperature Context triple: [Orcus, hasMeanSurfaceTemperature, around 40–50 K]
-
A.
hasAverageSurfaceTemperature
chosen
Indicates that an entity is associated with a specific mean value of its surface temperature over a defined period or condition.
-
B.
minSurfaceTemperature
Indicates the lowest temperature value observed or allowed on the surface of an object or environment.
-
C.
surfaceTemperature_K
Indicates the temperature of a surface expressed in kelvins.
-
D.
maxSurfaceTemperature
Indicates the highest temperature that the surface of an entity can reach or sustain under specified conditions.
-
E.
surfaceTemperatureRange
Indicates the range between the minimum and maximum surface temperatures observed or allowed for an entity.
- 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_69ad8b1341848190bd19dbf46892887d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9955e6488190bea170724d5fbfe8 |
completed | March 8, 2026, 3:44 p.m. |
| PD | Predicate disambiguation | batch_69ad960e71f8819088179d11248c6ed0 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:57 p.m.