Triple
T2598686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayelsa State |
E58292
|
entity |
| Predicate | hasLocalGovernmentArea |
P8215
|
FINISHED |
| Object | Nembe |
E106177
|
NE 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: Nembe | Statement: [Bayelsa State, hasLocalGovernmentArea, Nembe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nembe Context triple: [Bayelsa State, hasLocalGovernmentArea, Nembe]
-
A.
Nembe
chosen
Nembe is an Ijaw subgroup and town in Bayelsa State, Nigeria, known historically as a coastal trading center in the Niger Delta.
-
B.
Tamba
Tamba is a city located in Hyogo Prefecture, Japan, known for its rural landscapes, traditional pottery, and historical sites.
-
C.
Kukawa
Kukawa is a historic town in northeastern Nigeria that once served as the political and cultural center of the Kanuri people and the Bornu Empire.
-
D.
Nansio
Nansio is the main town and administrative center of Ukerewe Island in Lake Victoria, Tanzania.
-
E.
Olosega
Olosega is a small volcanic island in the Manuʻa group of American Samoa, known for its dramatic cliffs, lush vegetation, and connection by bridge to the neighboring island of Ofu.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ab4ac14040819098b13f4a27d5c8ff |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd4563b8c8190934616651e93654c |
completed | March 7, 2026, 7:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af83cc45f8819099d581725a53e527 |
completed | March 10, 2026, 2:37 a.m. |
Created at: March 6, 2026, 9:49 p.m.