Triple
T13956212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orthodox churches |
E335665
|
entity |
| Predicate | worldwideMembershipEstimate |
P14820
|
FINISHED |
| Object | over 200 million faithful |
—
|
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 200 million faithful | Statement: [Orthodox churches, worldwideMembershipEstimate, over 200 million faithful]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worldwideMembershipEstimate Context triple: [Orthodox churches, worldwideMembershipEstimate, over 200 million faithful]
-
A.
estimatedMemberCount
Indicates the approximate or predicted number of members associated with an entity.
-
B.
totalMembershipApprox
chosen
Indicates an approximate total count of members associated with an entity.
-
C.
memberAssociationCount
Indicates the number of associations or group memberships linked to a given member.
-
D.
approximateAudienceSize
Indicates an estimated number of individuals or entities that are expected to be reached or affected in a given context.
-
E.
numberOfPotentialMembers
Indicates the total count of entities that could potentially become members of a specified group or organization.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e78a4a481908e438745631a43c0 |
completed | April 14, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69de05a3ccf88190b45c742db483fa08 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:17 p.m.