Triple

T12099350
Position Surface form Disambiguated ID Type / Status
Subject Lekki E288149 entity
Predicate hasAttraction P105 FINISHED
Object Lekki Leisure Lake E55723 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: Lekki Leisure Lake | Statement: [Lekki, hasAttraction, Lekki Leisure Lake]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lekki Leisure Lake
Context triple: [Lekki, hasAttraction, Lekki Leisure Lake]
  • A. Mayow Park
    Mayow Park is a historic public green space in Sydenham, south London, featuring sports facilities, a playground, and landscaped gardens for community recreation.
  • B. Lekki Conservation Centre chosen
    Lekki Conservation Centre is a prominent nature reserve and ecotourism destination in Lagos, Nigeria, known for its rich biodiversity, elevated walkways, and one of Africa’s longest canopy walkways.
  • C. Lekki
    Lekki is a rapidly developing coastal city and affluent residential and commercial hub in Lagos State, Nigeria.
  • D. Lekki
    Lekki is the official mascot character created for the XVIII Olympic Winter Games.
  • E. Lekki
    Lekki is a fictional companion mascot character associated with Nokki, likely designed as a cute, supportive sidekick figure.
  • 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_69d6ab4964708190850585628b287b0c completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9155465388190bbe52453c9b11912 completed April 10, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f6724de481909fe29e3278136ea2 completed May 2, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:48 p.m.