Triple

T4121997
Position Surface form Disambiguated ID Type / Status
Subject Gulbuddin Hekmatyar E92633 entity
Predicate languageSpoken P151 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: [Gulbuddin Hekmatyar, languageSpoken, Dari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dari
Context triple: [Gulbuddin Hekmatyar, languageSpoken, 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. Bani
    Bani was a daughter of the prominent Indian freedom fighter and lawyer Chittaranjan (C. R.) Das.
  • E. Barshaini
    Barshaini is a small Himalayan village in Himachal Pradesh, India, that serves as a popular base and trailhead for treks into the Parvati Valley and surrounding high-altitude landscapes.
  • 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_69aed9685f70819086932777aec8d959 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69af020549dc8190a81a5dbbf70288c7 completed March 9, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b576b13cc881908fea25c686141546 completed March 14, 2026, 2:54 p.m.
Created at: March 9, 2026, 3:41 p.m.