Triple

T20086725
Position Surface form Disambiguated ID Type / Status
Subject Hiiraan E496151 entity
Predicate hasDistrict P459 FINISHED
Object Beledweyne District 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: Beledweyne District | Statement: [Hiiraan, hasDistrict, Beledweyne District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beledweyne District
Context triple: [Hiiraan, hasDistrict, Beledweyne District]
  • A. Beledweyne chosen
    Beledweyne is a prominent city in central Somalia that serves as a key commercial and administrative center in the Hiran region.
  • B. Aziziye district
    Aziziye district is an administrative district within Erzurum Province in eastern Turkey, known for its cold climate and proximity to the city of Erzurum.
  • C. Mansour District
    Mansour District is a prominent urban district in western Baghdad known for its residential neighborhoods, commercial centers, and diplomatic facilities.
  • D. Tanta District
    Tanta District is an administrative district in Egypt’s Gharbia Governorate that encompasses the city of Tanta and its surrounding areas.
  • E. Ain Shams district
    Ain Shams district is a densely populated residential and commercial neighborhood in northeastern Cairo, known as one of the city’s oldest urban areas.
  • 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_69da626eee3881909f3454986d4a6511 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6655ba40c8190adea0e271a1249cf completed April 20, 2026, 5:41 p.m.
Created at: April 11, 2026, 11:04 p.m.