Triple
T5137888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Hermon School for Boys |
E115871
|
entity |
| Predicate | hasDenominationalInfluence |
P59002
|
FINISHED |
| Object | Protestantism |
—
|
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: Protestantism | Statement: [Mount Hermon School for Boys, hasDenominationalInfluence, Protestantism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDenominationalInfluence Context triple: [Mount Hermon School for Boys, hasDenominationalInfluence, Protestantism]
-
A.
denominationalImpact
chosen
Indicates how a particular denomination influences, shapes, or affects another entity, group, or context.
-
B.
hasDenominationalUse
Indicates that something is used or applied within the context of a particular religious denomination or sect.
-
C.
hasDenominationalBackground
Indicates that an entity is associated with or originates from a particular religious denomination or tradition.
-
D.
hasDenominationalPresence
Indicates that a particular religious denomination is present or represented within a given location, organization, or context.
-
E.
doctrinalInfluenceOn
Indicates that one doctrine has influenced, shaped, or contributed to the development of another doctrine.
- 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_69bd44459a988190a772a5c2ec6a1965 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7fef2e8c8190982dd67f50295ada |
completed | March 20, 2026, 5:12 p.m. |
| PD | Predicate disambiguation | batch_69bd77ac2fc48190abeebb003a82384c |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:43 p.m.