Triple
T3024340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Nigeria |
E82540
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Asaba |
E254229
|
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: Asaba | Statement: [Southern Nigeria, contains, Asaba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asaba Context triple: [Southern Nigeria, contains, Asaba]
-
A.
Asaba
chosen
Asaba is the capital city of Delta State in southern Nigeria, situated on the western bank of the River Niger and serving as an important administrative and commercial center.
-
B.
Arugba
Arugba is the virgin priestess who carries sacrificial offerings to the Osun River during the annual Osun-Osogbo Festival in Nigeria.
-
C.
Ikeduru
Ikeduru is a local government area in southeastern Nigeria known for its predominantly Igbo population and its location within Imo State.
-
D.
Yakurr
Yakurr is a local government area in southeastern Nigeria known for its rich cultural heritage and predominantly agrarian communities.
-
E.
Makokou
Makokou is a small town in northeastern Gabon that serves as a key access point to the surrounding rainforest and protected areas.
- 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_69ad8b1fb34081908c1b873e2b7273e1 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9abac0288190a30b42674eea501f |
completed | March 8, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1deb342008190bec8fbaa4074d40c |
completed | March 11, 2026, 9:29 p.m. |
Created at: March 8, 2026, 3 p.m.