Triple

T2677221
Position Surface form Disambiguated ID Type / Status
Subject Epe E56488 entity
Predicate hasCoastlineOn P212 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: [Epe, hasCoastlineOn, Lekki Lagoon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lekki Lagoon
Context triple: [Epe, hasCoastlineOn, 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. Eso Ikoyi
    Eso Ikoyi were an elite warrior caste of the Oyo Empire in Yorubaland, renowned for their strict code of honor, bravery, and key role in the empire’s military campaigns.
  • 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_69ab4a4b13fc81909dfdb3f23da46832 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9b4a70481909d8b8242039c1cf2 completed March 7, 2026, 7:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69afbbb6de488190a0fb87efc7297ccb completed March 10, 2026, 6:35 a.m.
Created at: March 6, 2026, 9:54 p.m.