Triple
T8245279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevlar |
E192835
|
entity |
| Predicate | meltingBehavior |
P42113
|
FINISHED |
| Object | does not melt but decomposes |
—
|
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: does not melt but decomposes | Statement: [Kevlar, meltingBehavior, does not melt but decomposes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meltingBehavior Context triple: [Kevlar, meltingBehavior, does not melt but decomposes]
-
A.
meltingPoint
Indicates the temperature at which a substance changes from solid to liquid under specified conditions.
-
B.
materialMelted
Indicates that a material has undergone melting, transitioning from a solid to a liquid state.
-
C.
canMelt
Indicates that one entity has the capability to melt another entity or substance under appropriate conditions.
-
D.
hasMeltingMechanism
Indicates that an entity possesses a specific mechanism or process by which it melts or causes melting.
-
E.
isNonMelting
chosen
Indicates that the subject does not melt or transition to a liquid state under the relevant or specified conditions.
- 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_69ca82de7b8c81908d8106f8a53cff9b |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7872f6d481909ea1d3c2aad1a2b1 |
completed | March 31, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69cb36b437e881909958591357e83b9d |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:48 p.m.