Triple
T34812186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | councils of the Presbyterian Church (USA) |
E1003526
|
entity |
| Predicate | includeOffices |
P11900
|
FINISHED |
| Object | stated clerks at various levels |
—
|
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: stated clerks at various levels | Statement: [councils of the Presbyterian Church (USA), includeOffices, stated clerks at various levels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includeOffices Context triple: [councils of the Presbyterian Church (USA), includeOffices, stated clerks at various levels]
-
A.
includedOffice
chosen
Indicates that one office is contained within, or forms part of, another office or organizational unit.
-
B.
numberOfOffices
Indicates the total count of offices associated with a given entity.
-
C.
officeLocationsInclude
Indicates that the set of office locations associated with an entity includes a specified location as one of its members.
-
D.
mentionsOffice
Indicates that one entity explicitly refers to or brings up an office (such as a workplace, office location, or office role) in relation to another entity.
-
E.
hasOfficeType
Indicates that an entity’s office is classified as a specific type or category of office.
- 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_69f76db600b88190989abdf08fce3b27 |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fd7aac8190873077e63873aa72 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 3:59 p.m.