Triple
T28436899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Canadian Armoured Corps School |
E715291
|
entity |
| Predicate | trainsUnitsFrom |
P788
|
FINISHED |
| Object | Lord Strathcona’s Horse (Royal Canadians) |
—
|
NE NERFINISHED |
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: Lord Strathcona’s Horse (Royal Canadians) | Statement: [Royal Canadian Armoured Corps School, trainsUnitsFrom, Lord Strathcona’s Horse (Royal Canadians)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainsUnitsFrom Context triple: [Royal Canadian Armoured Corps School, trainsUnitsFrom, Lord Strathcona’s Horse (Royal Canadians)]
-
A.
transportUnit
Indicates a relationship where one entity serves as a means or unit for transporting another entity from one place to another.
-
B.
maintainsTrainsFor
Indicates that one entity is responsible for servicing, repairing, or otherwise keeping trains operational for another entity.
-
C.
trains
chosen
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
-
D.
trainsForOccupation
Indicates that an entity undergoes training or preparation aimed at qualifying for or performing a specific occupation.
-
E.
trainsCategory
Indicates that one entity is a category or type under which the other entity is trained or classified.
- 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_69efd6b253888190b3c7222ed6a403a8 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c2f81c8190bf369226306eef09 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 28, 2026, 1:43 a.m.