Triple
T823825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Marines |
E17807
|
entity |
| Predicate | distinctiveItem |
P662
|
FINISHED |
| Object | green beret |
—
|
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: green beret | Statement: [Royal Marines, distinctiveItem, green beret]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distinctiveItem Context triple: [Royal Marines, distinctiveItem, green beret]
-
A.
brandAttribute
Indicates that a specific attribute or characteristic is associated with, or describes, a particular brand.
-
B.
collectibleAspect
Indicates that one entity represents a collectible-related characteristic, feature, or dimension associated with another entity.
-
C.
wardrobeFeature
Indicates that a wardrobe possesses or includes a specific feature, attribute, or functional element.
-
D.
distinction
Indicates that one entity is recognized, treated, or classified as different or separate from another.
-
E.
characterizedBy
chosen
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
- 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ab7d3984819089aefbf12d3b3c2c |
completed | March 1, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69a4aa781e1081909df006f730296c53 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.