Triple
T9040280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rocky Ground |
E216605
|
entity |
| Predicate | hasGospelInfluence |
P44670
|
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: [Rocky Ground, hasGospelInfluence, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGospelInfluence Context triple: [Rocky Ground, hasGospelInfluence, true]
-
A.
isGospelInfluenced
chosen
Indicates that one entity (such as a work, style, or performance) is influenced in its characteristics, form, or content by gospel music or gospel traditions.
-
B.
doctrinalInfluenceOn
Indicates that one doctrine has influenced, shaped, or contributed to the development of another doctrine.
-
C.
influencedReligion
Indicates that one entity has had a shaping or modifying effect on the religious beliefs, practices, or traditions of another entity.
-
D.
influencedByReligion
Indicates that an entity’s characteristics, decisions, or development are shaped or affected by religious beliefs, practices, or institutions.
-
E.
missionaryInfluenceFrom
Indicates that one entity exerts religious or missionary influence upon another entity or location.
- 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_69ca83d22d488190adbce5e020e9cd1d |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc6b100a348190a59abd6e9b815c63 |
completed | April 1, 2026, 12:47 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee3597c81908919cf866ae95c24 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:09 p.m.