Triple
T26832818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 17th Regiment of (Light) Dragoons |
E675543
|
entity |
| Predicate | hasCavalryRole |
P180486
|
FINISHED |
| Object | reconnaissance |
—
|
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: reconnaissance | Statement: [17th Regiment of (Light) Dragoons, hasCavalryRole, reconnaissance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCavalryRole Context triple: [17th Regiment of (Light) Dragoons, hasCavalryRole, reconnaissance]
-
A.
hasCavalrySetting
Indicates that an entity is associated with a context, configuration, or environment specifically involving cavalry.
-
B.
hasCavalryHeritage
Indicates that an entity has a historical or traditional connection to cavalry forces or mounted military service.
-
C.
hasHeraldicRole
Indicates that an entity holds or is assigned a specific role or function within a heraldic context (such as in coats of arms, armorial bearings, or heraldic ceremonies).
-
D.
hasRoyalGuard
Indicates that an entity is protected or served by a designated royal guard or group of royal guards.
-
E.
hasCargoRole
Indicates that an entity participates in a cargo-related capacity or function within a transport, shipment, or logistics context.
- F. None of above. chosen
Provenance (4 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_69eee9b776448190993a60b67fcc9545 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69f7431aac148190bb6aac59817c174a |
completed | May 3, 2026, 12:44 p.m. |
Created at: April 27, 2026, 5:02 a.m.