Triple

T22734567
Position Surface form Disambiguated ID Type / Status
Subject Oruzgan E562228 entity
Predicate hasDistrict P459 FINISHED
Object Chora 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: Chora District | Statement: [Oruzgan, hasDistrict, Chora District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chora District
Context triple: [Oruzgan, hasDistrict, Chora District]
  • A. Chora District chosen
    Chora District is an administrative district located within Afghanistan’s central Uruzgan Province.
  • B. Patnos District
    Patnos District is an administrative district in eastern Turkey known for its rural settlements and location within Ağrı Province.
  • C. Didim District
    Didim District is an administrative district in Aydın Province, southwestern Turkey, known for its coastal tourism centers and nearby ancient sites such as the Temple of Apollo at Didyma.
  • D. Gazipaşa District
    Gazipaşa District is an administrative district in Antalya Province, Turkey, known for its Mediterranean coastline, agricultural production, and growing tourism centered around the town of Gazipaşa.
  • E. Zangiota District
    Zangiota District is an administrative district in eastern Uzbekistan, located within the Tashkent Region and encompassing both urban and rural settlements.
  • 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.