Triple
T19076966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canadian Indian residential school system |
E466928
|
entity |
| Predicate | numberOfChildrenAttended |
P134252
|
FINISHED |
| Object | over 150000 |
—
|
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: over 150000 | Statement: [Canadian Indian residential school system, numberOfChildrenAttended, over 150000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfChildrenAttended Context triple: [Canadian Indian residential school system, numberOfChildrenAttended, over 150000]
-
A.
numberOfChildren
Indicates the total count of children that an entity has.
-
B.
childrenWith
Indicates that two or more entities share one or more children together as parents or guardians.
-
C.
numberOfAdoptedChildren
Indicates the count of children that an entity has legally adopted.
-
D.
childrenFounded
Indicates that the subject’s children established, created, or founded the object entity (such as an organization, institution, or project).
-
E.
adoptedChildren
Indicates that one entity has legally taken another entity as their child through adoption.
- 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_69d8dd04f4488190b1121cc53ef2bfd6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e2e5591081908a4f8e4b2011b408 |
completed | April 20, 2026, 8:25 a.m. |
| PD | Predicate disambiguation | batch_69e4b99f602881909eeb9c780597e0e6 |
completed | April 19, 2026, 11:16 a.m. |
| PDg | Predicate description generation | batch_69e4bfe8a06081909fd5c28a33e9f218 |
completed | April 19, 2026, 11:43 a.m. |
Created at: April 10, 2026, 12:04 p.m.