Triple
T16008809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T-800 |
E388285
|
entity |
| Predicate | hasDurability |
P38321
|
FINISHED |
| Object | high resistance to damage |
—
|
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: high resistance to damage | Statement: [T-800, hasDurability, high resistance to damage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDurability Context triple: [T-800, hasDurability, high resistance to damage]
-
A.
durabilityClass
chosen
Indicates the level or category of resistance an entity has to wear, damage, or degradation over time.
-
B.
durabilityModel
Indicates a relationship where an entity is associated with a specific model or method used to estimate or characterize its durability over time or under certain conditions.
-
C.
durabilityLossRate
Indicates the rate at which an entity’s durability decreases over time or use.
-
D.
durabilityLossCondition
Indicates the specific circumstances or events under which an object's durability decreases.
-
E.
mechanicalDurability
Indicates the ability of something to withstand mechanical forces, stresses, or wear without failing or degrading.
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142dc081c819082527e3fa8773460 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:55 a.m.