Triple
T9610314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sharps Chapel, Tennessee |
E232079
|
entity |
| Predicate | hasReligionPresence |
P6676
|
FINISHED |
| Object | Christian churches |
—
|
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: Christian churches | Statement: [Sharps Chapel, Tennessee, hasReligionPresence, Christian churches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligionPresence Context triple: [Sharps Chapel, Tennessee, hasReligionPresence, Christian churches]
-
A.
hasDenominationalPresence
Indicates that a particular religious denomination is present or represented within a given location, organization, or context.
-
B.
hasAssociatedReligion
Indicates that an entity is connected with or linked to a particular religion.
-
C.
religionsPresent
chosen
Indicates that one or more religions are present, practiced, or represented in relation to a given entity or context.
-
D.
hasReligiousOrganization
Indicates that an entity is associated with, governed by, or belongs to a specific religious organization.
-
E.
religiousGroupsPresent
Indicates that one or more religious groups are present or represented in a given context, location, or situation.
- 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_69ca8485a90c819094fe40b42fde9d70 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9a85d4c881909ccab2e972d97e68 |
completed | April 1, 2026, 10:21 p.m. |
| PD | Predicate disambiguation | batch_69ccd5a6fd2481908efd131e207b8143 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:08 p.m.