Triple
T12800206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Twenty Sermons |
E305996
|
entity |
| Predicate | associatedWithClergyRole |
P3092
|
FINISHED |
| Object | Episcopal clergyman |
—
|
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: Episcopal clergyman | Statement: [Twenty Sermons, associatedWithClergyRole, Episcopal clergyman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithClergyRole Context triple: [Twenty Sermons, associatedWithClergyRole, Episcopal clergyman]
-
A.
memberOfClergy
Indicates that one entity serves in an official religious or clerical role within a religious organization or institution.
-
B.
hasClergyType
chosen
Indicates the specific category or role of clergy associated with an entity.
-
C.
hasClergy
Indicates that an organization or institution possesses or is served by members of the clergy.
-
D.
ecclesiasticalRole
Indicates that one entity holds or is assigned a specific religious or church-related office, function, or position in relation to another entity.
-
E.
involvesClergy
Indicates that the situation, event, or action includes the participation or presence of clergy members.
- 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_69d7bdf366888190a8cccb982606889c |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e7d3f5c8190bf01bef5d263ca26 |
completed | April 10, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69d9640ed7448190b276e7fab649f7d2 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:30 p.m.