Triple
T15435198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bishop of Los Angeles |
E369740
|
entity |
| Predicate | religiousStyle |
P21942
|
FINISHED |
| Object | My Lord Bishop |
—
|
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: My Lord Bishop | Statement: [Bishop of Los Angeles, religiousStyle, My Lord Bishop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousStyle Context triple: [Bishop of Los Angeles, religiousStyle, My Lord Bishop]
-
A.
religiousSpectrum
Indicates a relationship that places entities along a range or continuum of religious belief, practice, or affiliation.
-
B.
religiousElement
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
-
C.
religiousGenre
chosen
Indicates that the subject is associated with or categorized under a religious genre, style, or tradition.
-
D.
religiousMood
Indicates a prevailing emotional or spiritual atmosphere associated with religious experience, practice, or devotion between entities.
-
E.
religiousAttitude
Indicates an entity’s stance, disposition, or orientation toward religion or religious beliefs.
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03edb3ec481908b26164d4470c9bc |
completed | April 16, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69ded27f45548190a6d2b1b85cb47444 |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:21 a.m.