Triple

T22281995
Position Surface form Disambiguated ID Type / Status
Subject Khadir District E550755 entity
Predicate subdivisionName1 P12497 FINISHED
Object Daykundi Province 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: Daykundi Province | Statement: [Khadir District, subdivisionName1, Daykundi Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daykundi Province
Context triple: [Khadir District, subdivisionName1, Daykundi Province]
  • A. Daykundi Province chosen
    Daykundi Province is a central Afghan province known for its predominantly Hazara population and mountainous terrain.
  • B. Faryab Province
    Faryab Province is a region in northern Afghanistan known for its ethnically diverse population, agricultural economy, and strategic location bordering Turkmenistan.
  • C. Rehamna Province
    Rehamna Province is an administrative division in central Morocco known for its rural communities and agricultural activities within the Marrakesh-Safi region.
  • D. Sar-e Pol Province
    Sar-e Pol Province is a northern Afghan province known for its ethnically diverse population, agriculture-based economy, and history of conflict and insecurity.
  • E. Golestan Province
    Golestan Province is a northeastern region of Iran known for its ethnic diversity, rich natural landscapes, and location along the Caspian Sea.
  • 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_69e11e44d538819097c6b8f333af3352 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f14eac0994819088e39a1b5d39cf18 completed April 29, 2026, 12:19 a.m.
Created at: April 16, 2026, 8:40 p.m.