Triple

T1770407
Position Surface form Disambiguated ID Type / Status
Subject Sukki E38860 entity
Predicate hasSiblingMascot P30548 FINISHED
Object Lekki E195384 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 | Statement: [Sukki, hasSiblingMascot, Lekki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lekki
Context triple: [Sukki, hasSiblingMascot, Lekki]
  • A. Lekki
    Lekki is the official mascot character created for the XVIII Olympic Winter Games.
  • B. Lekki chosen
    Lekki is a fictional companion mascot character associated with Nokki, likely designed as a cute, supportive sidekick figure.
  • C. Harpurhey
    Harpurhey is an inner-city district of Manchester, England, known for its dense residential areas and local shopping precincts.
  • D. Wuse
    Wuse is a prominent commercial and residential district in Nigeria’s capital city, Abuja, known for its bustling markets, businesses, and government offices.
  • E. Ibadan
    Ibadan is one of the largest and most populous cities in southwestern Nigeria, historically significant as a major Yoruba cultural and economic center.
  • 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_69a8862e61708190af97b9838cc3f5de completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa648eb9488190b1be2d2b6d259634 completed March 6, 2026, 5:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69adbf4fd0ec8190904f1ad2155c58bf completed March 8, 2026, 6:26 p.m.
Created at: March 4, 2026, 7:31 p.m.