Triple

T930957
Position Surface form Disambiguated ID Type / Status
Subject Voice of America E20090 entity
Predicate languageOfWorkOrName P15 FINISHED
Object Dari
Dari is a variety of the Persian language primarily spoken in Afghanistan and used in media, education, and government there.
 E109613 NE FINISHED

How this triple was built (4 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: [Voice of America, languageOfWorkOrName, Dari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dari
Context triple: [Voice of America, languageOfWorkOrName, Dari]
  • A. Dila
    Dila is the commonly used short name for FC Dila Gori, a professional football club based in Gori, Georgia.
  • B. 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.
  • C. Nasar
    Nasar is a surname most notably associated with Sylvia Nasar, the economist and author of "A Beautiful Mind."
  • D. Mardan
    Mardan is a major city in northern Pakistan known as an important commercial and cultural center of the Khyber Pakhtunkhwa province.
  • E. Jowhar
    Jowhar is a town in southern Somalia that serves as the capital of the Middle Shabelle region and an important agricultural and administrative center.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Dari
Triple: [Voice of America, languageOfWorkOrName, Dari]
Generated description
Dari is a variety of the Persian language primarily spoken in Afghanistan and used in media, education, and government there.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dari
Target entity description: Dari is a variety of the Persian language primarily spoken in Afghanistan and used in media, education, and government there.
  • A. Dila
    Dila is the commonly used short name for FC Dila Gori, a professional football club based in Gori, Georgia.
  • B. 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.
  • C. Nasar
    Nasar is a surname most notably associated with Sylvia Nasar, the economist and author of "A Beautiful Mind."
  • D. Mardan
    Mardan is a major city in northern Pakistan known as an important commercial and cultural center of the Khyber Pakhtunkhwa province.
  • E. Jowhar
    Jowhar is a town in southern Somalia that serves as the capital of the Middle Shabelle region and an important agricultural and administrative center.
  • F. None of above. chosen

Provenance (5 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_69a493af3dc48190adb7263e6e445ea1 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b34b302c81908fa32cb18f551493 completed March 1, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7ee1108188190a26c73864c697061 completed March 4, 2026, 8:32 a.m.
NEDg Description generation batch_69a7f1a1214481909538745d5713e402 completed March 4, 2026, 8:47 a.m.
NED2 Entity disambiguation (via description) batch_69a7f2303534819094ae764b20d223ee completed March 4, 2026, 8:49 a.m.
Created at: March 1, 2026, 7:40 p.m.