Triple

T1247908
Position Surface form Disambiguated ID Type / Status
Subject Taliban E26807 entity
Predicate secondaryLanguageUsed P9103 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: [Taliban, secondaryLanguageUsed, Dari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dari
Context triple: [Taliban, secondaryLanguageUsed, 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. Dila
    Dila is the commonly used short name for FC Dila Gori, a professional football club based in Gori, Georgia.
  • C. Sana'i
    Sana'i was a pioneering 12th-century Persian Sufi poet whose mystical and didactic works profoundly shaped later poets, including Rumi.
  • D. Haditha
    Haditha is a city in western Iraq known for its strategic location along the Euphrates River and its nearby hydroelectric dam and reservoir.
  • E. Gulnare
    Gulnare is a central female character in Lord Byron’s narrative poem "The Corsair," known for her courage, passion, and pivotal role in the story’s dramatic events.
  • 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_69a49487a9c48190ba9b05348fd1b53f completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4bf827e088190a16d845cea14f2c9 completed March 1, 2026, 10:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac93c420f08190a6eda4d0aa498a3a completed March 7, 2026, 9:08 p.m.
Created at: March 1, 2026, 7:47 p.m.