Triple

T3077310
Position Surface form Disambiguated ID Type / Status
Subject Lagos State E64168 entity
Predicate hasCity P316 FINISHED
Object Apapa E56227 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: Apapa | Statement: [Lagos State, hasCity, Apapa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Apapa
Context triple: [Lagos State, hasCity, Apapa]
  • A. Apapa Port chosen
    Apapa Port is Nigeria’s largest and busiest seaport complex, serving as a major gateway for the country’s international maritime trade in Lagos.
  • B. Owan
    Owan is an ethnic group in southern Nigeria, primarily inhabiting parts of Edo State and known for its distinct language and cultural traditions.
  • 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. Owo
    Owo is a prominent Yoruba sub-group in southwestern Nigeria, known for its rich cultural heritage, traditional art, and historical kingdom centered in present-day Ondo State.
  • E. Zaria
    Zaria is a historic city in northern Nigeria known as an important center of Hausa culture, Islamic scholarship, and 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_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_69b1f88d32a08190b4e18da4b26b534c completed March 11, 2026, 11:19 p.m.
Created at: March 8, 2026, 3:02 p.m.