Triple

T1000291
Position Surface form Disambiguated ID Type / Status
Subject Sima Samar E21586 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: [Sima Samar, languageSpoken, Dari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dari
Context triple: [Sima Samar, 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. Dila
    Dila is the commonly used short name for FC Dila Gori, a professional football club based in Gori, Georgia.
  • C. 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.
  • D. Nasar
    Nasar is a surname most notably associated with Sylvia Nasar, the economist and author of "A Beautiful Mind."
  • E. Mardan
    Mardan is a major city in northern Pakistan known as an important commercial and cultural center of the Khyber Pakhtunkhwa province.
  • 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_69a493c476b48190b41fc5e793171cc6 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b4fb18b88190ae2d620aaaff4f90 completed March 1, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac2a1aab68819091537958818fce48 completed March 7, 2026, 1:37 p.m.
Created at: March 1, 2026, 7:41 p.m.