Triple
T12070336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bose gas |
E287406
|
entity |
| Predicate | hasCriticalTemperature |
P103043
|
FINISHED |
| Object | Bose–Einstein condensation critical temperature |
—
|
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: Bose–Einstein condensation critical temperature | Statement: [Bose gas, hasCriticalTemperature, Bose–Einstein condensation critical temperature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCriticalTemperature Context triple: [Bose gas, hasCriticalTemperature, Bose–Einstein condensation critical temperature]
-
A.
hasTemperature
Indicates that an entity possesses or is characterized by a specific temperature value.
-
B.
hasEffectiveTemperature
Indicates that an entity (typically a star or other astronomical object) possesses a specific effective surface temperature characterizing its emitted radiation.
-
C.
hasTemperatureRegime
Indicates that an entity is characterized by or associated with a particular pattern or regime of temperature conditions.
-
D.
hasTemperatureCategory
Indicates that an entity is associated with a specific qualitative temperature classification (e.g., hot, cold, warm).
-
E.
hasMinTemperature
Indicates that something possesses or is associated with a specified minimum temperature value.
- 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bda47c8190b94860b31df4a98c |
completed | April 10, 2026, 2:01 p.m. |
| PDg | Predicate description generation | batch_69d91006e14081909838412df082f794 |
completed | April 10, 2026, 2:58 p.m. |
Created at: April 8, 2026, 9:48 p.m.