Triple
T25704421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Book II (Joseph Andrews) |
E644546
|
entity |
| Predicate | hasClericalCharacter |
P107701
|
FINISHED |
| Object | Parson Adams |
—
|
NE NERFINISHED |
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: Parson Adams | Statement: [Book II (Joseph Andrews), hasClericalCharacter, Parson Adams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClericalCharacter Context triple: [Book II (Joseph Andrews), hasClericalCharacter, Parson Adams]
-
A.
hasClericalProtagonist
chosen
Indicates that the main character in the work is a member of the clergy or holds a religious office.
-
B.
isCleric
Indicates that an entity holds the role or status of a cleric, typically serving a religious or spiritual function.
-
C.
hasClericalMember
Indicates that an entity includes or is associated with a member who performs clerical or administrative duties.
-
D.
hasClericalFunction
Indicates that an entity performs, is responsible for, or is associated with a clerical or administrative function.
-
E.
isClericIn
Indicates that an entity serves or functions as a cleric within a specified organization, location, or 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_69e77e83c8ec8190bf52fcdac4838984 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f650c70d7c819093d9a0f005f7c8d5 |
completed | May 2, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69f64cab1f648190a2a9460690d18a37 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 21, 2026, 9:01 p.m.