Triple
T12467107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oru West |
E297951
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Mgbidi |
E984770
|
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: Mgbidi | Statement: [Oru West, hasSettlement, Mgbidi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mgbidi Context triple: [Oru West, hasSettlement, Mgbidi]
-
A.
Mgbidi
chosen
Mgbidi is a town in Imo State, southeastern Nigeria, known as a local government and commercial center in the region.
-
B.
Kibibi
Kibibi is a lively and energetic host character in Disney's "Festival of the Lion King" stage show at Disney theme parks.
-
C.
Mbaïki
Mbaïki is a town in the Central African Republic that serves as an important regional center southwest of the capital, Bangui.
-
D.
Mbanderu
Mbanderu is a subgroup of the Herero people with its own distinct dialect and cultural traditions, primarily found in Namibia and Botswana.
-
E.
Bongo–Bagirmi
Bongo–Bagirmi is a subgroup of Central Sudanic languages spoken primarily in parts of Central Africa, including Chad and neighboring regions.
- 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94db979c481908778188794b2c08e |
completed | April 10, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64ba3983c8190aef5e3b6a6d2e41e |
completed | May 2, 2026, 7:08 p.m. |
Created at: April 8, 2026, 9:56 p.m.