Triple
T17059389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mackenzie–Papineau Battalion |
E413913
|
entity |
| Predicate | recognizedAsVeteransInYear |
P125690
|
FINISHED |
| Object | 2001 |
—
|
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: 2001 | Statement: [Mackenzie–Papineau Battalion, recognizedAsVeteransInYear, 2001]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recognizedAsVeteransInYear Context triple: [Mackenzie–Papineau Battalion, recognizedAsVeteransInYear, 2001]
-
A.
isVeteranOf
Indicates that an entity has previously served in and been discharged from a specified military conflict, campaign, or armed force.
-
B.
yearsOfMilitaryService
Indicates the number of years an entity has served or is recorded as serving in the military.
-
C.
serviceNumberOrYearsOfService
Indicates a relationship that specifies either an entity’s service identification number or the duration of time the entity has served.
-
D.
veteransLater
Indicates that one event, state, or action involving veterans occurs after another in time.
-
E.
personReferredToMilitaryService
Indicates that one person has directed, recommended, or assigned another person to perform military service.
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3db7c21a881909bfb67080706612f |
completed | April 18, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69e35d60a588819084f53ef9f8b2e7c0 |
completed | April 18, 2026, 10:30 a.m. |
| PDg | Predicate description generation | batch_69e3753f93c88190808fec5692f66699 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:34 a.m.