Triple
T399977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bigelow Chapel |
E9257
|
entity |
| Predicate | isReligiousBuilding |
P916
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Bigelow Chapel, isReligiousBuilding, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isReligiousBuilding Context triple: [Bigelow Chapel, isReligiousBuilding, true]
-
A.
hasPlaceOfWorship
Indicates that an entity possesses, contains, or is associated with a designated location used for religious or spiritual worship.
-
B.
hasReligiousSite
chosen
Indicates that a location or entity possesses, contains, or is associated with a religious site such as a temple, church, mosque, shrine, or similar place of worship.
-
C.
religiousTarget
Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
-
D.
religiousFunction
Indicates that one entity serves a religious role, purpose, or function in relation to another entity.
-
E.
religiousElement
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
- 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_69a2e8004cb88190b92ed1add6abf41a |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ec8e655c819081eff85c0ef55fa5 |
completed | Feb. 28, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69a2e96d17d08190878d3a68b17d51ca |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.