Triple
T17059398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mackenzie–Papineau Battalion |
E413913
|
entity |
| Predicate | volunteersFrom |
P125691
|
FINISHED |
| Object | English-speaking Canadians |
—
|
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: English-speaking Canadians | Statement: [Mackenzie–Papineau Battalion, volunteersFrom, English-speaking Canadians]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: volunteersFrom Context triple: [Mackenzie–Papineau Battalion, volunteersFrom, English-speaking Canadians]
-
A.
receivedVolunteersFrom
Indicates that one entity accepted or was provided with volunteers originating from another entity.
-
B.
volunteerLabel
Indicates that an entity is identified or tagged as a volunteer in relation to another entity or context.
-
C.
volunteeredFor
Indicates that an entity willingly offered their time or services to support or participate in an activity, cause, or organization.
-
D.
typeOfVolunteerUnit
Indicates that one entity is a specific kind or category of volunteer unit in relation to another entity.
-
E.
hasAdultVolunteers
Indicates that an entity is associated with one or more adult individuals who volunteer their time or services for it.
- 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.