Triple
T829049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CARE |
E17922
|
entity |
| Predicate | memberOrganizationsCount |
P276
|
FINISHED |
| Object | 14 |
—
|
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: 14 | Statement: [CARE, memberOrganizationsCount, 14]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memberOrganizationsCount Context triple: [CARE, memberOrganizationsCount, 14]
-
A.
numberOfAssociateMembers
Indicates the total count of associate members linked to a given entity.
-
B.
hasNumberOfMemberInstitutions
chosen
Indicates the quantitative count of member institutions associated with a given entity.
-
C.
organizationAssociatedWith
Indicates that there is a formal or recognized connection or affiliation between an organization and another entity.
-
D.
numberOfBoardMembers
Indicates the total count of individuals who serve as members on a board.
-
E.
massOrganization
Indicates a relationship where an organization is characterized as a mass organization, typically involving broad-based, large-scale membership or participation.
- 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ab9b458881909aa23f0eb7cbc87f |
completed | March 1, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69a4aa79a6488190a634388e071ed9b7 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.