Triple
T270351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oldtown Folks |
E5618
|
entity |
| Predicate | hasReligiousContent |
P2154
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Oldtown Folks, hasReligiousContent, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousContent Context triple: [Oldtown Folks, hasReligiousContent, yes]
-
A.
religiousElement
chosen
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
-
B.
hadViewOnReligion
Indicates that an entity held a particular perspective, belief, or stance regarding religion.
-
C.
recognizesReligion
Indicates that one entity formally acknowledges or accepts another entity as a valid or legitimate religion.
-
D.
religiousRestriction
Indicates that one entity imposes, experiences, or is subject to limitations or rules based on religious beliefs or practices in relation to another entity or context.
-
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_69a25853594c8190b05ec3a586ec88bf |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25e69a9248190b9e7959b43223baa |
completed | Feb. 28, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69a25b721180819080d43c43fcbccf87 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:57 a.m.