Triple
T2439376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diocese of Alabama |
E53236
|
entity |
| Predicate | numberOfMembersApproximate |
P31691
|
FINISHED |
| Object | over 30,000 |
—
|
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 30,000 | Statement: [Diocese of Alabama, numberOfMembersApproximate, over 30,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMembersApproximate Context triple: [Diocese of Alabama, numberOfMembersApproximate, over 30,000]
-
A.
numberOfFullMembers
Indicates the total count of entities that hold full membership status within a specified group or organization.
-
B.
numberOfMembersReturned
Indicates the quantity of members that are provided or yielded as a result of an operation or query.
-
C.
originalNumberOfMembers
Indicates the initial total count of members in a group or organization before any changes such as additions or removals.
-
D.
numberOfAssociateMembers
Indicates the total count of associate members linked to a given entity.
-
E.
numberOfGroupMembers
chosen
Indicates the total count of individual members that belong to a specified group.
- 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_69ab495b6dac8190ac82661aa1452222 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abcebf7cac8190889e6890d72c256c |
completed | March 7, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69abc5ac11b081908ce6a506e81a742a |
completed | March 7, 2026, 6:29 a.m. |
Created at: March 6, 2026, 9:43 p.m.