Triple

T16693877
Position Surface form Disambiguated ID Type / Status
Subject Nur Muhammad Taraki E405661 entity
Predicate languageOfWorkOrName P15 FINISHED
Object Dari E109613 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: Dari | Statement: [Nur Muhammad Taraki, languageOfWorkOrName, Dari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dari
Context triple: [Nur Muhammad Taraki, languageOfWorkOrName, Dari]
  • A. Dari chosen
    Dari is a variety of the Persian language primarily spoken in Afghanistan and used in media, education, and government there.
  • B. Dijlah
    Dijlah is the Arabic name for the Tigris River, one of the major rivers of Western Asia flowing through Turkey, Syria, and Iraq.
  • C. Dairut
    Dairut is a city in Upper Egypt known as an important urban and agricultural center within the Asyut region along the Nile.
  • D. Daudin
    Daudin is a French surname most notably associated with François Marie Daudin, an 18th-century zoologist and herpetologist.
  • E. Dawar
    Dawar is a town in the Gurez Valley of Jammu and Kashmir, India, known for its remote Himalayan setting near the Line of Control.
  • 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_69d8838db21081909589220fd71440a4 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37eab93a081909aedc45f3f8f0e10 completed April 18, 2026, 12:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00919acd308190a3f29040554b9cfc completed May 10, 2026, 2:09 p.m.
Created at: April 10, 2026, 5:19 a.m.