Triple

T14701538
Position Surface form Disambiguated ID Type / Status
Subject Potiskum E345311 entity
Predicate hasNearbyCity P350 FINISHED
Object Maiduguri E60433 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: Maiduguri | Statement: [Potiskum, hasNearbyCity, Maiduguri]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maiduguri
Context triple: [Potiskum, hasNearbyCity, Maiduguri]
  • A. Maiduguri chosen
    Maiduguri is a major city in northeastern Nigeria that serves as the capital of Borno State and a key economic and administrative center in the region.
  • B. Dutse
    Dutse is a city in northern Nigeria that serves as the administrative and economic center of Jigawa State.
  • C. Dutse
    Dutse is a locality within Nigeria’s Federal Capital Territory, situated in the Bwari Area Council on the outskirts of Abuja.
  • D. Sokoto
    Sokoto is a historic city in northwestern Nigeria that served as the capital of the Sokoto Caliphate and remains an important cultural and Islamic scholarly center.
  • E. Kano
    Kano is a long-running Mortal Kombat villain known as a ruthless mercenary and leader of the Black Dragon crime syndicate, often depicted with a cybernetic eye and expertise in knives and dirty fighting tactics.
  • 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_69fe24a996708190834733bfc669c3d3 completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:28 a.m.