Triple

T20198974
Position Surface form Disambiguated ID Type / Status
Subject Arthur & George E493160 entity
Predicate tvAdaptationStars P41102 FINISHED
Object Arsher Ali NE NERFINISHED

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: Arsher Ali | Statement: [Arthur & George, tvAdaptationStars, Arsher Ali]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arsher Ali
Context triple: [Arthur & George, tvAdaptationStars, Arsher Ali]
  • A. Arsher Ali chosen
    Arsher Ali is a British actor known for his work in film, television, and theatre, including roles in projects such as the horror film "The Ritual."
  • B. Shehzad Khan
    Shehzad Khan is an Indian film and television actor best known for his supporting and comic roles in Hindi cinema, including the classic romance "Qayamat Se Qayamat Tak."
  • C. Khalid Ashraf
    Khalid Ashraf is a computer scientist and deep learning researcher known for co-designing the efficient convolutional neural network architecture SqueezeNet.
  • D. Shia Irfan
    Shia Irfan is a spiritual and philosophical tradition within Shia Islam that emphasizes inner knowledge, mystical insight, and esoteric interpretation of religious teachings.
  • E. Salman Amin Khan
    Salman Amin Khan is an American educator and entrepreneur best known as the founder of Khan Academy, a nonprofit organization providing free online educational resources worldwide.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6269614c8190bb40475d9d477358 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66d8c0eac81908ffdf72d71d2e5d2 completed April 20, 2026, 6:16 p.m.
Created at: April 11, 2026, 11:37 p.m.