Triple

T3077296
Position Surface form Disambiguated ID Type / Status
Subject Lagos State E64168 entity
Predicate largestCity P235 FINISHED
Object 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: Lagos | Statement: [Lagos State, largestCity, Lagos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lagos
Context triple: [Lagos State, largestCity, Lagos]
  • A. 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.
  • B. Lagos
    Lagos is a historic coastal city in Portugal’s Algarve region, known for its scenic beaches, dramatic cliffs, and well-preserved old town.
  • C. Ibadan
    Ibadan is one of the largest and most populous cities in southwestern Nigeria, historically significant as a major Yoruba cultural and economic center.
  • D. Port Harcourt
    Port Harcourt is a major oil and industrial city in southern Nigeria and the capital of Rivers State.
  • E. Benin City
    Benin City is a major urban center in southern Nigeria, historically known as the capital of the ancient Benin Kingdom and renowned for its rich cultural heritage and bronze artworks.
  • 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_69ad857a8aec8190bfdfd9c14554ac5a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada1a6f6148190ae5cd6e45eda9006 completed March 8, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69b333feff988190831b50d87892b9c1 completed March 12, 2026, 9:45 p.m.
Created at: March 8, 2026, 3:02 p.m.