Triple
T37491274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gliese 581b |
E931692
|
entity |
| Predicate | equilibriumTemperatureCategory |
P100818
|
FINISHED |
| Object | too hot for liquid water on surface |
—
|
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: too hot for liquid water on surface | Statement: [Gliese 581b, equilibriumTemperatureCategory, too hot for liquid water on surface]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equilibriumTemperatureCategory Context triple: [Gliese 581b, equilibriumTemperatureCategory, too hot for liquid water on surface]
-
A.
equilibriumTemperature
Indicates the temperature at which a system’s heat exchange balances so that no net change in its thermal state occurs.
-
B.
equilibriumTemperatureRelativeToEarth
Indicates the equilibrium temperature of an object or system expressed in relation to, or normalized by, Earth’s equilibrium temperature.
-
C.
hasEffectiveTemperature
Indicates that an entity (typically a star or other astronomical object) possesses a specific effective surface temperature characterizing its emitted radiation.
-
D.
surfaceTemperature_K
Indicates the temperature of a surface expressed in kelvins.
-
E.
hasTemperatureCategory
chosen
Indicates that an entity is associated with a specific qualitative temperature classification (e.g., hot, cold, warm).
- 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_69f76ec457a4819094eeb3aed9baac11 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba68077788190b311e027435fcf87 |
completed | May 6, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fba34c65ac8190b298f0f00d1dcc0e |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.