Triple
T2970196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VIS 100 |
E80259
|
entity |
| Predicate | operatingTemperatureRange |
P3958
|
FINISHED |
| Object | military-standard environmental conditions |
—
|
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: military-standard environmental conditions | Statement: [VIS 100, operatingTemperatureRange, military-standard environmental conditions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatingTemperatureRange Context triple: [VIS 100, operatingTemperatureRange, military-standard environmental conditions]
-
A.
operatingTemperature
chosen
Indicates the range or specific value of temperature within which an entity is designed or allowed to function properly.
-
B.
growthTemperatureRange
Indicates the range of temperatures within which an organism or entity can grow or function effectively.
-
C.
surfaceTemperatureRange
Indicates the range between the minimum and maximum surface temperatures observed or allowed for an entity.
-
D.
operationalRange
Indicates the span of conditions (such as distance, time, or environment) within which a system, device, or process can function effectively and safely.
-
E.
hasTemperature
Indicates that an entity possesses or is characterized by a specific temperature value.
- 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_69ad8b14ffe881908ffed62f9595c867 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad997282b481909d078be0e70d9930 |
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, 2:58 p.m.