Triple

T13036102
Position Surface form Disambiguated ID Type / Status
Subject 42 (school) E326563 entity
Predicate hasCampus P116 FINISHED
Object 42 Lagos E10118 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: 42 Lagos | Statement: [42 (school), hasCampus, 42 Lagos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 42 Lagos
Context triple: [42 (school), hasCampus, 42 Lagos]
  • A. Lagos
    Lagos is a historic coastal city in Portugal’s Algarve region, known for its scenic beaches, dramatic cliffs, and well-preserved old town.
  • B. Lagos chosen
    Lagos is a major coastal megacity in southwestern Nigeria, known as the country’s economic hub and one of Africa’s most populous and vibrant urban centers.
  • C. Yaba
    Yaba is a bustling commercial and residential district on Lagos Mainland in Nigeria, known for its markets, educational institutions, and growing tech startup scene.
  • D. Lagos Mainland
    Lagos Mainland is a densely populated urban area of Lagos, Nigeria, known for its residential neighborhoods, commercial hubs, and vibrant cultural life distinct from the more upscale Lagos Island.
  • E. Badagry
    Badagry is a coastal town in southwestern Nigeria historically known as a major slave port and trading center during the transatlantic slave trade.
  • 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_69d8076cc45c81908123123f43e69266 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97f2a71a0819098bb6cf8a4b2208a completed April 10, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbcf11f88190ab1746f973132af1 completed May 3, 2026, 4:15 a.m.
Created at: April 9, 2026, 8:55 p.m.