Triple
T5474786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Household Brigade |
E122922
|
entity |
| Predicate | hasUniformFeature |
P2930
|
FINISHED |
| Object | bearskin caps for Foot Guards |
—
|
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: bearskin caps for Foot Guards | Statement: [Household Brigade, hasUniformFeature, bearskin caps for Foot Guards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUniformFeature Context triple: [Household Brigade, hasUniformFeature, bearskin caps for Foot Guards]
-
A.
hasFeature
Indicates that an entity possesses, exhibits, or includes a particular characteristic, attribute, or component.
-
B.
hasFeatureCode
Indicates that an entity is associated with a specific feature identifier or code that characterizes one of its properties or attributes.
-
C.
hasDistinctFeature
Indicates that an entity possesses a specific characteristic or attribute that differentiates it from others.
-
D.
hasFeatureID
Indicates that an entity is associated with a specific feature identified by a unique ID.
-
E.
usesUniform
chosen
Indicates that one entity regularly wears or employs a standardized set of clothing or equipment designated as a uniform.
- 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_69bd46459ff48190823377457bcf7128 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd9232ded08190b4142e604319b2ba |
completed | March 20, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69bd91a58c448190904964a439045e05 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:09 p.m.