Triple

T5709422
Position Surface form Disambiguated ID Type / Status
Subject Hazarajat E125866 entity
Predicate historicalProvince P915 FINISHED
Object Daykundi Province E129309 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: Daykundi Province | Statement: [Hazarajat, historicalProvince, Daykundi Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daykundi Province
Context triple: [Hazarajat, historicalProvince, 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. Golestan Province
    Golestan Province is a northeastern region of Iran known for its ethnic diversity, rich natural landscapes, and location along the Caspian Sea.
  • E. South Khorasan Province
    South Khorasan Province is an eastern Iranian province formed from the historical region of Khorasan, known for its deserts, saffron production, and border with Afghanistan.
  • 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_69c0082d6fe48190b777fb383769e5c8 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0248c3dac8190824fca9ddde89665 completed March 22, 2026, 5:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c097e866088190bc7e820226d6a8fd completed March 23, 2026, 1:31 a.m.
Created at: March 22, 2026, 3:46 p.m.