Triple

T6760874
Position Surface form Disambiguated ID Type / Status
Subject Congo Town Airport E154587 entity
Predicate serves P98 FINISHED
Object Congo Town E157124 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: Congo Town | Statement: [Congo Town Airport, serves, Congo Town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Congo Town
Context triple: [Congo Town Airport, serves, Congo Town]
  • A. Congo Town chosen
    Congo Town is a small settlement on South Andros in The Bahamas, known as a local administrative and transportation hub with its own regional airport.
  • B. Afrikanisches Viertel
    Afrikanisches Viertel is a Berlin neighborhood known for its streets named after African countries and figures, reflecting Germany’s colonial history and ongoing debates about decolonization and memory.
  • C. Orangi Town
    Orangi Town is a densely populated residential area in Karachi, Pakistan, known as one of Asia’s largest informal settlements.
  • D. Zaman Town
    Zaman Town is a residential neighborhood located within the Korangi District of Karachi, Pakistan.
  • E. Marcus Garvey Village
    Marcus Garvey Village is a large mid-20th-century affordable housing complex in Brownsville, Brooklyn, known for its distinctive low-rise, courtyard-centered design.
  • 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_69c688109c1c8190added9a221292af0 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d212c31881909dfe8ca9de69acf7 completed March 27, 2026, 6:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c712b352d08190932bc99dd3d673ba completed March 27, 2026, 11:28 p.m.
Created at: March 27, 2026, 2:12 p.m.