Triple
T12204548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BDU |
E290802
|
entity |
| Predicate | materialBlend |
P56833
|
FINISHED |
| Object | 50/50 nylon-cotton ripstop |
—
|
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: 50/50 nylon-cotton ripstop | Statement: [BDU, materialBlend, 50/50 nylon-cotton ripstop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: materialBlend Context triple: [BDU, materialBlend, 50/50 nylon-cotton ripstop]
-
A.
materialCompatibility
Indicates that two or more materials are suitable to be used together without causing adverse interactions, degradation, or performance issues.
-
B.
materialEffect
Indicates that one material causes, influences, or brings about a change in the properties, behavior, or state of another material or system.
-
C.
materialParameter
chosen
Indicates a relationship where a specific parameter or property is associated with, or characterizes, a material in a given context.
-
D.
materialOptions
Indicates that there are one or more possible materials that can be chosen or applied in relation to a given entity or context.
-
E.
typicalBlendStyle
Indicates the usual or characteristic way in which two or more elements are combined or mixed together.
- 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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d938cd2edc8190b1971349dbc0dee0 |
completed | April 10, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69d91c38321c819080d500d0d64a04f6 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:51 p.m.