Triple

T14001203
Position Surface form Disambiguated ID Type / Status
Subject Lagos State Government E336828 entity
Predicate capital P234 FINISHED
Object Ikeja NE NERFINISHED

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: Ikeja | Statement: [Lagos State Government, capital, Ikeja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ikeja
Context triple: [Lagos State Government, capital, Ikeja]
  • A. Ikeja chosen
    Ikeja is a major commercial and administrative hub in Nigeria, serving as the capital of Lagos State and hosting numerous businesses, government offices, and the Murtala Muhammed International Airport.
  • B. Kōtō
    Kōtō is a special ward in eastern Tokyo, Japan, known for its mix of residential neighborhoods, waterfront areas, and commercial districts.
  • C. Hachiōji
    Hachiōji is a city in western Tokyo, Japan, known as a regional commercial and educational hub with rich historical sites and access to nearby mountains and nature.
  • D. Musashino
    Musashino is a suburban city in western Tokyo, Japan, known for the popular Kichijoji district and its blend of residential neighborhoods, shopping areas, and parks.
  • E. Toshima
    Toshima is a special ward in northwest Tokyo known for the major commercial and entertainment hub of Ikebukuro and its dense urban residential districts.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d81c645c5c8190b1fd16a285a1b78a completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ed06a50819093ddc64f55050689 completed April 14, 2026, 12:10 p.m.
Created at: April 9, 2026, 10:19 p.m.