Triple
T929756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RCRC Movement |
E20063
|
entity |
| Predicate | numberOfNationalSocieties |
P21516
|
FINISHED |
| Object | 191 |
—
|
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: 191 | Statement: [RCRC Movement, numberOfNationalSocieties, 191]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfNationalSocieties Context triple: [RCRC Movement, numberOfNationalSocieties, 191]
-
A.
hasNumberOfMemberInstitutions
Indicates the quantitative count of member institutions associated with a given entity.
-
B.
numberOfMainCommittees
Indicates the total count of primary or main committees associated with an entity.
-
C.
hasTechnicalSociety
Indicates that an entity is associated with, or possesses membership in, a technical or engineering-focused society or organization.
-
D.
associatedConfederationCount
Indicates the number of distinct confederations with which an entity is associated.
-
E.
numberOfAssociateMembers
Indicates the total count of associate members linked to a given entity.
- 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_69a493af3dc48190adb7263e6e445ea1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b349b3d0819090c58b4fb60c6a1b |
completed | March 1, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69a4b29876348190a29f4ff9878074a5 |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b2f4e3fc81908c8a2d1fbef9c5d2 |
completed | March 1, 2026, 9:43 p.m. |
Created at: March 1, 2026, 7:40 p.m.