Triple
T5575953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Africa Inland Mission |
E146318
|
entity |
| Predicate | hasMinistryContext |
P64534
|
FINISHED |
| Object | urban areas |
—
|
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: urban areas | Statement: [Africa Inland Mission, hasMinistryContext, urban areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMinistryContext Context triple: [Africa Inland Mission, hasMinistryContext, urban areas]
-
A.
belongsToMinistry
Indicates that one entity is under the authority, administration, or organizational control of a specific ministry.
-
B.
hasMinistries
Indicates that an entity possesses, oversees, or is organized into one or more ministries as subordinate units or departments.
-
C.
hasMediaMinistry
Indicates that an entity operates, oversees, or is associated with a ministry or department responsible for media-related affairs.
-
D.
hasLayMinistry
Indicates that an entity participates in or is associated with a lay (non-ordained) ministry role or service within a religious context.
-
E.
supportedMinistryOf
Indicates that one entity provided assistance, endorsement, or resources to help carry out the ministry or religious service activities of another entity.
- F. None of above. chosen
Provenance (4 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_69c008ffed108190a084602227af6157 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c02067e8d8819090a006cb266da5fe |
completed | March 22, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69c01b147cc081909237f3f2967d4cb8 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f0684908190ae2d14f0bd2ab892 |
completed | March 22, 2026, 4:55 p.m. |
Created at: March 22, 2026, 3:37 p.m.