Triple
T6397126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unruh effect |
E143967
|
entity |
| Predicate | thermalStateFor |
P70397
|
FINISHED |
| Object | uniformly accelerated observers |
—
|
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: uniformly accelerated observers | Statement: [Unruh effect, thermalStateFor, uniformly accelerated observers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thermalStateFor Context triple: [Unruh effect, thermalStateFor, uniformly accelerated observers]
-
A.
hasTemperature
Indicates that an entity possesses or is characterized by a specific temperature value.
-
B.
temperatureDependent
Indicates that the existence, intensity, or outcome of a relationship or process varies as a function of temperature.
-
C.
hasTemperatureRegime
Indicates that an entity is characterized by or associated with a particular pattern or regime of temperature conditions.
-
D.
thermalControl
Indicates a relationship where one entity regulates, adjusts, or maintains the temperature or thermal conditions of another entity or environment.
-
E.
hasThermalActivity
Indicates that an entity exhibits or is associated with heat-related phenomena such as heating, cooling, or temperature change.
- 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_69c008db906c819096f3597d55d95432 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06896d180819091548a728e903184 |
completed | March 22, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69c060f25c088190b433f78553ff1d84 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623d23448190a75cf5d802fc0a02 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:35 p.m.