Triple
T2694199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rivers State |
E58472
|
entity |
| Predicate | ethnicGroup |
P194
|
FINISHED |
| Object | Ikwerre |
E77303
|
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: Ikwerre | Statement: [Rivers State, ethnicGroup, Ikwerre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ikwerre Context triple: [Rivers State, ethnicGroup, Ikwerre]
-
A.
Ikwerre
chosen
Ikwerre is a Niger-Congo language spoken primarily by the Ikwerre people in Rivers State, Nigeria, particularly in and around Port Harcourt.
-
B.
Ndowe
Ndowe is a Bantu language spoken by the Ndowe people along the coastal region of Equatorial Guinea.
-
C.
Ewondo
Ewondo is a Bantu language spoken primarily by the Ewondo people in central Cameroon, including in and around the capital city, Yaoundé.
-
D.
Ogbia
Ogbia is a local government area in Bayelsa State, Nigeria, known for its oil-rich communities and as the birthplace of former Nigerian President Goodluck Jonathan.
-
E.
Iluka
Iluka is a small coastal town in northern New South Wales, Australia, known for its beaches, fishing, and proximity to the Clarence River and Iluka Nature Reserve.
- 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_69ab4ac269e481909cb317d79e68b75b |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda10a9bc81908473d02ab9116cef |
completed | March 7, 2026, 7:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc030c9b88190934f96a8ff74c4a7 |
completed | March 10, 2026, 6:54 a.m. |
Created at: March 6, 2026, 9:55 p.m.