Triple
T2336806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1st Hussars |
E44328
|
entity |
| Predicate | hasRegimentalColour |
P15387
|
FINISHED |
| Object | Guidon bearing battle honours |
—
|
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: Guidon bearing battle honours | Statement: [1st Hussars, hasRegimentalColour, Guidon bearing battle honours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegimentalColour Context triple: [1st Hussars, hasRegimentalColour, Guidon bearing battle honours]
-
A.
corpsColour
chosen
Indicates the specific color associated with a military corps or unit.
-
B.
hasSchoolColours
Indicates that an entity is associated with one or more official colours that represent it, typically in formal or symbolic contexts.
-
C.
hasInsigniaWornBy
Indicates that a particular insignia is worn by a specified entity (such as a person, group, or organization).
-
D.
ribbonColours
Indicates that there is an association between an entity and one or more colours of ribbons related to it.
-
E.
hasTypeOfInsignia
Indicates that an entity bears or is associated with a specific kind or category of insignia.
- 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_69a889132b488190bbb43ad4780ddd92 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abc6f75d888190a2e41edaa532e83f |
completed | March 7, 2026, 6:34 a.m. |
| PD | Predicate disambiguation | batch_69abc594087c819098100a10c5478a4b |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:51 p.m.