Triple
T2706049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kapton |
E59343
|
entity |
| Predicate | hasContinuousUseTemperature |
P3958
|
FINISHED |
| Object | up to about 260 °C |
—
|
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: up to about 260 °C | Statement: [Kapton, hasContinuousUseTemperature, up to about 260 °C]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasContinuousUseTemperature Context triple: [Kapton, hasContinuousUseTemperature, up to about 260 °C]
-
A.
hasTemperature
Indicates that an entity possesses or is characterized by a specific temperature value.
-
B.
operatingTemperature
chosen
Indicates the range or specific value of temperature within which an entity is designed or allowed to function properly.
-
C.
hasThermalActivity
Indicates that an entity exhibits or is associated with heat-related phenomena such as heating, cooling, or temperature change.
-
D.
usesThermals
Indicates that one entity relies on rising warm air currents (thermals) as a means to gain lift, move, or maintain altitude.
-
E.
temperatureControlMethod
Indicates the method or mechanism used to regulate or maintain a desired temperature.
- 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_69ab4ac66bc88190b9e4afa5fc843f72 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda559a908190ad5d92c11a398a03 |
completed | March 7, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69abd82062988190b4292f242ad70b2c |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:55 p.m.