Triple

T11578710
Position Surface form Disambiguated ID Type / Status
Subject Lagos Lagoon E274569 entity
Predicate connectedTo P37 FINISHED
Object Lekki Lagoon E288149 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 Lagoon | Statement: [Lagos Lagoon, connectedTo, Lekki Lagoon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lekki Lagoon
Context triple: [Lagos Lagoon, connectedTo, Lekki Lagoon]
  • A. Lekki
    Lekki is the official mascot character created for the XVIII Olympic Winter Games.
  • B. Lekki chosen
    Lekki is a rapidly developing coastal city and affluent residential and commercial hub in Lagos State, Nigeria.
  • C. Lekki
    Lekki is a fictional companion mascot character associated with Nokki, likely designed as a cute, supportive sidekick figure.
  • D. Lekki Conservation Centre
    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.
  • E. 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.
  • 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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8904b46288190890ecafd6ceb0c3d completed April 10, 2026, 5:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69e714080a60819095205355776c8637 completed April 21, 2026, 6:07 a.m.
Created at: April 8, 2026, 9:38 p.m.