Triple

T22734569
Position Surface form Disambiguated ID Type / Status
Subject Oruzgan E562228 entity
Predicate hasDistrict P459 FINISHED
Object Gizab 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: Gizab District | Statement: [Oruzgan, hasDistrict, Gizab District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gizab District
Context triple: [Oruzgan, hasDistrict, Gizab District]
  • A. Gizab District
    Gizab District is an administrative district located within Daykundi Province in central Afghanistan.
  • B. Gizab District chosen
    Gizab District is an administrative district located within Uruzgan Province in central Afghanistan, known for its mountainous terrain and history of conflict.
  • C. Siyazan District
    Siyazan District is an administrative region in northeastern Azerbaijan known for its location along the Caspian Sea coast and its role in the country’s oil and agricultural sectors.
  • D. Yesil District
    Yesil District is a central administrative district of Astana, Kazakhstan, known for hosting major landmarks and modern developments in the capital.
  • E. Eğil District
    Eğil District is an administrative district in southeastern Turkey known for its ancient historical sites and scenic location along the Tigris River within Diyarbakır Province.
  • 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_69e24550859c81908727d91efc3a81b4 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1796f030881908e141564d442bd1b completed April 29, 2026, 3:22 a.m.
Created at: April 17, 2026, 3:22 p.m.