Triple
T37546502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apologia Pro Vita Sua |
E933477
|
entity |
| Predicate | describesEarlierRole |
P7222
|
FINISHED |
| Object | Anglican priest |
—
|
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: Anglican priest | Statement: [Apologia Pro Vita Sua, describesEarlierRole, Anglican priest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: describesEarlierRole Context triple: [Apologia Pro Vita Sua, describesEarlierRole, Anglican priest]
-
A.
earlierOccupation
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
-
B.
mayHavePriorRole
Indicates that an entity is allowed or expected to have held a specified role at some earlier time.
-
C.
economicRolePast
Indicates that an entity previously held a specific economic function, position, or role in the past.
-
D.
roleInExperience
Indicates the specific function, position, or part an entity plays within a particular experience or event.
-
E.
describesCareerOf
chosen
Indicates that one entity provides a description or characterization of the professional career of another entity.
- 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_69f76eca55bc8190acf25741793d5dac |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fdd5fba5048190b7d430ae2054a1fd |
completed | May 8, 2026, 12:24 p.m. |
| PD | Predicate disambiguation | batch_69fdd35f76f88190a1854ea27132f9c7 |
completed | May 8, 2026, 12:13 p.m. |
Created at: May 3, 2026, 4:17 p.m.