Triple

T22229320
Position Surface form Disambiguated ID Type / Status
Subject Sikandar Kher E549425 entity
Predicate notableWork P4 FINISHED
Object Aarya
Aarya is an Indian crime drama web series that follows a woman drawn into the criminal underworld after her husband's death.
 E1525268 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: Aarya | Statement: [Sikandar Kher, notableWork, Aarya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Aarya
Context triple: [Sikandar Kher, notableWork, Aarya]
  • A. Aradhana
    Aradhana is a landmark 1969 Hindi romantic drama film, celebrated for its music and performances, that significantly boosted the stardom of its lead actors.
  • B. Damini
    Damini is a critically acclaimed 1993 Indian Hindi-language courtroom drama film directed by Rajkumar Santoshi, known for its powerful portrayal of a woman's fight for justice.
  • C. Aditi
    Aditi is a Vedic mother goddess in Hindu mythology, revered as the personification of boundlessness and the mother of many deities.
  • D. Tarpeena
    Tarpeena is a small rural town and locality in South Australia, known historically for its timber and forestry industries.
  • E. Sanam
    Sanam is an archaeological site in Sudan’s Napatan region, known for its ancient Kushite remains and its inclusion in the UNESCO-listed Gebel Barkal and associated sites.
  • 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: Aarya
Triple: [Sikandar Kher, notableWork, Aarya]
Generated description
Aarya is an Indian crime drama web series that follows a woman drawn into the criminal underworld after her husband's death.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Aarya
Target entity description: Aarya is an Indian crime drama web series that follows a woman drawn into the criminal underworld after her husband's death.
  • A. Aradhana
    Aradhana is a landmark 1969 Hindi romantic drama film, celebrated for its music and performances, that significantly boosted the stardom of its lead actors.
  • B. Damini
    Damini is a critically acclaimed 1993 Indian Hindi-language courtroom drama film directed by Rajkumar Santoshi, known for its powerful portrayal of a woman's fight for justice.
  • C. Aditi
    Aditi is a Vedic mother goddess in Hindu mythology, revered as the personification of boundlessness and the mother of many deities.
  • D. Tarpeena
    Tarpeena is a small rural town and locality in South Australia, known historically for its timber and forestry industries.
  • E. Sanam
    Sanam is an archaeological site in Sudan’s Napatan region, known for its ancient Kushite remains and its inclusion in the UNESCO-listed Gebel Barkal and associated sites.
  • 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_69e11e4102b881909cf47d3768e25c19 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12bf173308190a3d21bfc59b39728 completed April 28, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0aae75b2ac819083289b84fd3b6dd7 completed May 18, 2026, 6:15 a.m.
NEDg Description generation batch_6a0aaf211d8481908e7c23e35e920e87 completed May 18, 2026, 6:18 a.m.
NED2 Entity disambiguation (via description) batch_6a0ab01b5cd48190bf67942798e4db45 completed May 18, 2026, 6:22 a.m.
Created at: April 16, 2026, 8:37 p.m.