Triple
T35067100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duncan Trussell |
E1011759
|
entity |
| Predicate | religiousOrPhilosophicalInterest |
P102165
|
FINISHED |
| Object | Buddhism |
—
|
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: Buddhism | Statement: [Duncan Trussell, religiousOrPhilosophicalInterest, Buddhism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousOrPhilosophicalInterest Context triple: [Duncan Trussell, religiousOrPhilosophicalInterest, Buddhism]
-
A.
religionOrBelief
Indicates that one entity holds, practices, or is associated with a particular religion, faith, or belief system.
-
B.
religiousScholarship
Indicates a relationship where an entity provides or is associated with financial or institutional support specifically for religious study or education.
-
C.
religiousSpectrum
Indicates a relationship that places entities along a range or continuum of religious belief, practice, or affiliation.
-
D.
associatedReligionOrBelief
chosen
Indicates that an entity is connected to, identified with, or characterized by a particular religion or belief system.
-
E.
religiousTopicAddressed
Indicates that a subject deals with, discusses, or focuses on a religious theme, issue, or question.
- 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_69f76dd193108190af2528186f25b72a |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff9b1ad27081908f8a492396950795 |
completed | May 9, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69ff9a6354c48190ae21070c1424cb7a |
completed | May 9, 2026, 8:34 p.m. |
Created at: May 3, 2026, 4:01 p.m.