Triple
T2706048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kapton |
E59343
|
entity |
| Predicate | hasThermalStabilityUpTo |
P3958
|
FINISHED |
| Object | approximately 400 °C in air |
—
|
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: approximately 400 °C in air | Statement: [Kapton, hasThermalStabilityUpTo, approximately 400 °C in air]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThermalStabilityUpTo Context triple: [Kapton, hasThermalStabilityUpTo, approximately 400 °C in air]
-
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.
temperatureDependent
Indicates that the existence, intensity, or outcome of a relationship or process varies as a function of temperature.
-
D.
meltingPoint
Indicates the temperature at which a substance changes from solid to liquid under specified conditions.
-
E.
hasStabilityLevel
Indicates that something possesses a particular degree or state of stability, often quantified or categorized along a defined scale.
- 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.