Triple
T28244539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lubemba |
E712127
|
entity |
| Predicate | hasSubChiefdoms |
P747
|
FINISHED |
| Object | various Bemba chiefdoms |
—
|
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: various Bemba chiefdoms | Statement: [Lubemba, hasSubChiefdoms, various Bemba chiefdoms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubChiefdoms Context triple: [Lubemba, hasSubChiefdoms, various Bemba chiefdoms]
-
A.
hasSubChiefs
Indicates that an entity holds a chief position that has one or more subordinate chiefs reporting to it.
-
B.
hasNumberOfSubdistricts
Indicates the relationship specifying how many subdistricts are associated with a given entity.
-
C.
hasSubdivision
chosen
Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
-
D.
hasTerritorialSubdivisionType
Indicates that an entity’s territorial subdivisions are of a specified administrative or geographic type (e.g., province, county, district).
-
E.
hasSuburbanMunicipality
Indicates that one administrative region includes or is associated with a municipality located in a suburban area.
- 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_69efb51fb98881909692421959ec0170 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69fd19f791f48190bbb6f6047f9ddc59 |
completed | May 7, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69fd0df365948190bc9bfc7ffd46acd8 |
completed | May 7, 2026, 10:10 p.m. |
Created at: April 27, 2026, 11 p.m.