Triple
T33843765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alo |
E867422
|
entity |
| Predicate | hasNeighboringChiefdom |
P200524
|
FINISHED |
| Object | Sigave |
—
|
NE NERFINISHED |
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: Sigave | Statement: [Alo, hasNeighboringChiefdom, Sigave]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNeighboringChiefdom Context triple: [Alo, hasNeighboringChiefdom, Sigave]
-
A.
hasNeighbouringDivision
Indicates that one division is directly adjacent to and shares a boundary with another division.
-
B.
hasNeighbouringAdministrativeUnitType
Indicates that one administrative unit is directly adjacent to another administrative unit of a specified type.
-
C.
hasNeighboringLGA
Indicates that one local government area is geographically adjacent to or directly borders another local government area.
-
D.
neighboringTownship
Indicates that two townships share a common boundary and are directly adjacent to each other.
-
E.
hasNearbyProvince
Indicates that one province is geographically close to or directly adjacent to another province.
- 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_69f349937b648190a34ada70f6a2b534 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff9361943c81909544203cbc998a69 |
completed | May 9, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69ff913138a08190b59bdc9d8d199eb3 |
completed | May 9, 2026, 7:55 p.m. |
| PDg | Predicate description generation | batch_69ff935f48808190aa6f4834f59d45b8 |
completed | May 9, 2026, 8:04 p.m. |
Created at: May 1, 2026, 1:47 a.m.