Triple
T24121396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Coleman |
E597664
|
entity |
| Predicate | religionOfVictim |
P45
|
FINISHED |
| Object | Episcopal (Jonathan M. Daniels) |
—
|
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: Episcopal (Jonathan M. Daniels) | Statement: [Tom Coleman, religionOfVictim, Episcopal (Jonathan M. Daniels)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religionOfVictim Context triple: [Tom Coleman, religionOfVictim, Episcopal (Jonathan M. Daniels)]
-
A.
declaredReligion
Indicates that an entity has formally stated or reported a particular religious affiliation.
-
B.
religionOfPerpetrators
Indicates the religious affiliation or belief system associated with the individuals who carried out a particular act or offense.
-
C.
religiousAffiliation
chosen
Indicates that one entity has a specified religious association, belief system, or denominational membership.
-
D.
ethnicReligion
Indicates that a religion is closely associated with a particular ethnic group, often tied to that group’s culture, ancestry, or identity.
-
E.
religiousTarget
Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
- 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_69e288c74200819098ab875b592cb39f |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1dee47d5481909d61b8d948a24aa8 |
completed | April 29, 2026, 10:35 a.m. |
| PD | Predicate disambiguation | batch_69f1765650fc8190a6bc1eb512b240bf |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 11:05 p.m.