Triple
T14717158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eggon |
E345710
|
entity |
| Predicate | localGovernmentAreaInhabited |
P74637
|
FINISHED |
| Object | Nasarawa Eggon |
E368501
|
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: Nasarawa Eggon | Statement: [Eggon, localGovernmentAreaInhabited, Nasarawa Eggon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nasarawa Eggon Context triple: [Eggon, localGovernmentAreaInhabited, Nasarawa Eggon]
-
A.
Nasarawa Eggon
chosen
Nasarawa Eggon is a town and administrative local government area in central Nigeria known for its diverse ethnic communities and agricultural activities.
-
B.
Nasarawa
Nasarawa is a town and Local Government Area in central Nigeria’s Nasarawa State, known historically as part of the former Nasarawa Emirate.
-
C.
Nasarawa State
Nasarawa State is a centrally located state in Nigeria known for its diverse ethnic groups, agricultural activities, and proximity to the Federal Capital Territory, Abuja.
-
D.
Nkwerre
Nkwerre is a town and local government area in southeastern Nigeria known for its location within Imo State and its cultural and commercial activities.
-
E.
Igbesa
Igbesa is a prominent town in Ogun State, Nigeria, known for its growing industrial presence and educational institutions.
- 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_69d822e5911c8190ba589f957dbd9ba7 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb98688f48190b2b19ce7aa06a6db |
completed | April 14, 2026, 10:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdf0935f088190b54f2e106532972a |
completed | May 8, 2026, 2:17 p.m. |
Created at: April 10, 2026, 1:29 a.m.