Triple
T8245283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevlar |
E192835
|
entity |
| Predicate | tensileModulus |
P58822
|
FINISHED |
| Object | on the order of 70–130 GPa |
—
|
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: on the order of 70–130 GPa | Statement: [Kevlar, tensileModulus, on the order of 70–130 GPa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tensileModulus Context triple: [Kevlar, tensileModulus, on the order of 70–130 GPa]
-
A.
mechanicalProperty
chosen
Indicates a relationship where a mechanical characteristic (such as strength, stiffness, hardness, or elasticity) is attributed to or associated with an entity.
-
B.
thermalExpansionCoefficient
Indicates how much a material's size changes per unit length (or volume) for each degree change in temperature.
-
C.
hasTension
Indicates the presence of strain, stress, or conflict between entities in their relationship or interaction.
-
D.
hardnessMohs
Indicates the relative hardness of a material as measured on the Mohs scale of mineral hardness.
-
E.
thermalConductivity
Indicates how effectively heat is conducted through a material per unit temperature gradient.
- 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.