Triple

T11805646
Position Surface form Disambiguated ID Type / Status
Subject Baldia Town E280739 entity
Predicate hasRoadConnectionTo P11435 FINISHED
Object Orangi Town E280151 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: Orangi Town | Statement: [Baldia Town, hasRoadConnectionTo, Orangi Town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orangi Town
Context triple: [Baldia Town, hasRoadConnectionTo, Orangi Town]
  • A. Orangi Town chosen
    Orangi Town is a densely populated residential area in Karachi, Pakistan, known as one of Asia’s largest informal settlements.
  • B. Zaman Town
    Zaman Town is a residential neighborhood located within the Korangi District of Karachi, Pakistan.
  • C. Congo Town
    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.
  • D. Congo Town
    Congo Town is a coastal suburb of Monrovia in Liberia, known as a residential and commercial area within Montserrado County.
  • E. Bilal Town
    Bilal Town is a residential suburb of Abbottabad, Pakistan, internationally known as the neighborhood where Osama bin Laden was found and killed by U.S. forces in 2011.
  • 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_69d6ab26aae88190b2489efcb2a24234 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5c8324481909a54852a9bb714e0 completed April 10, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69f1315b4b1481908106984a1362be89 completed April 28, 2026, 10:14 p.m.
Created at: April 8, 2026, 9:42 p.m.