Triple
T6315433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ebonyi State |
E141603
|
entity |
| Predicate | largestCity |
P235
|
FINISHED |
| Object | Abakaliki |
E584952
|
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: Abakaliki | Statement: [Ebonyi State, largestCity, Abakaliki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abakaliki Context triple: [Ebonyi State, largestCity, Abakaliki]
-
A.
Abakaliki
chosen
Abakaliki is a major city in southeastern Nigeria known as an administrative, commercial, and agricultural hub.
-
B.
Enugu
Enugu is a major city in southeastern Nigeria known historically for its coal mining industry and role as a regional administrative and economic center.
-
C.
Bauchi
Bauchi is a prominent city in northeastern Nigeria that serves as the capital of Bauchi State and a key commercial and administrative center in the region.
-
D.
Makurdi
Makurdi is the capital city of Benue State in central Nigeria, serving as an important administrative and commercial hub in the region.
-
E.
Keffi
Keffi is a historic town and commercial center in central Nigeria that serves as one of the key urban settlements in Nasarawa State.
- 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_69c008d13b8c8190be47d896eb735605 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c064a197488190946c4637b3c829a5 |
completed | March 22, 2026, 9:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6040714988190abbbadb4039966ef |
completed | March 27, 2026, 4:13 a.m. |
Created at: March 22, 2026, 4:28 p.m.