Triple
T14701537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Potiskum |
E345311
|
entity |
| Predicate | hasNearbyCity |
P350
|
FINISHED |
| Object | Bauchi |
E66827
|
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: Bauchi | Statement: [Potiskum, hasNearbyCity, Bauchi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bauchi Context triple: [Potiskum, hasNearbyCity, Bauchi]
-
A.
Bauchi
chosen
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.
-
B.
Makurdi
Makurdi is the capital city of Benue State in central Nigeria, serving as an important administrative and commercial hub in the region.
-
C.
Kaduna
Kaduna is a major industrial and political center in northern Nigeria, known for its diverse population and role as the capital of Kaduna State.
-
D.
Auchi
Auchi is a prominent town in southern Nigeria known as a commercial and educational hub within Edo State.
-
E.
Ekiti
Ekiti are a subgroup of the Yoruba people of southwestern Nigeria, known for their distinct dialect, rich cultural traditions, and strong emphasis on education.
- 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_69d822e4a8c08190a155df736bb7bc13 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb605f5948190ab6b20887c4b6833 |
completed | April 14, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69febfcf67348190862c65faa1c815f0 |
completed | May 9, 2026, 5:02 a.m. |
Created at: April 10, 2026, 1:28 a.m.