Triple

T19613362
Position Surface form Disambiguated ID Type / Status
Subject Population Council E470789 entity
Predicate hasOfficeIn P1268 FINISHED
Object Accra NE NERFINISHED

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: Accra | Statement: [Population Council, hasOfficeIn, Accra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Accra
Context triple: [Population Council, hasOfficeIn, Accra]
  • A. Accra chosen
    Accra is the capital and largest city of Ghana, known as a major economic, political, and cultural hub in West Africa.
  • B. Koforidua
    Koforidua is a major city in southern Ghana known as an administrative, commercial, and transportation hub for the Eastern Region.
  • C. Takoradi
    Takoradi is a coastal city in southwestern Ghana that developed into a key commercial and industrial hub, particularly known for its deep-water seaport and role in regional trade.
  • D. Kumasi
    Kumasi is a major city in southern Ghana, known as the historic capital of the Ashanti Kingdom and a key cultural and commercial center in West Africa.
  • E. Serekunda
    Serekunda is the most populous urban center and a major commercial hub in The Gambia.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e510fa248190b7afb274a1d4cf73 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e640cd5de48190a9f7bab4da3f5b5a completed April 20, 2026, 3:05 p.m.
Created at: April 10, 2026, 1:43 p.m.