Triple

T20417436
Position Surface form Disambiguated ID Type / Status
Subject Jhankaar Beats E500748 entity
Predicate hasCharacter P2308 FINISHED
Object Neel
Neel is a central character in the Hindi musical comedy film "Jhankaar Beats," known for his role in the story’s exploration of friendship, music, and urban life.
 E1428945 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: Neel | Statement: [Jhankaar Beats, hasCharacter, Neel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Neel
Context triple: [Jhankaar Beats, hasCharacter, Neel]
  • A. Neela
    Neela is a prominent commander in the monkey kingdom of Kishkindha in the Indian epic Ramayana, known for his leadership in Rama’s campaign against Ravana.
  • B. Neela
    Neela is a central street racer and love interest in the film "The Fast and the Furious: Tokyo Drift," known for her drifting skills in Tokyo's underground racing scene.
  • C. Neels
    Neels is a given name and surname of Dutch or Afrikaans origin, commonly used in South Africa and the Netherlands.
  • D. Nalneesh Neel
    Nalneesh Neel is an Indian actor known for his character roles in Hindi films and web series, including the adaptation of "The White Tiger."
  • E. Neea
    Neea is a genus of flowering plants in the four o'clock family, comprising mostly tropical trees and shrubs native to the Americas.
  • 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: Neel
Triple: [Jhankaar Beats, hasCharacter, Neel]
Generated description
Neel is a central character in the Hindi musical comedy film "Jhankaar Beats," known for his role in the story’s exploration of friendship, music, and urban life.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Neel
Target entity description: Neel is a central character in the Hindi musical comedy film "Jhankaar Beats," known for his role in the story’s exploration of friendship, music, and urban life.
  • A. Neela
    Neela is a central street racer and love interest in the film "The Fast and the Furious: Tokyo Drift," known for her drifting skills in Tokyo's underground racing scene.
  • B. Neela
    Neela is a prominent commander in the monkey kingdom of Kishkindha in the Indian epic Ramayana, known for his leadership in Rama’s campaign against Ravana.
  • C. Neels
    Neels is a given name and surname of Dutch or Afrikaans origin, commonly used in South Africa and the Netherlands.
  • D. Nalneesh Neel
    Nalneesh Neel is an Indian actor known for his character roles in Hindi films and web series, including the adaptation of "The White Tiger."
  • E. Neea
    Neea is a genus of flowering plants in the four o'clock family, comprising mostly tropical trees and shrubs native to the Americas.
  • 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_69e0b4a935588190b9446a99b37ced44 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67a44ecf48190ba5a3872af500dc8 completed April 20, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a087b284bb8819090f76ec27116c619 completed May 16, 2026, 2:11 p.m.
NEDg Description generation batch_6a088017be588190ab94b8180e44ebf4 completed May 16, 2026, 2:32 p.m.
NED2 Entity disambiguation (via description) batch_6a0880c45e1081908f439ade0c31a47e completed May 16, 2026, 2:35 p.m.
Created at: April 16, 2026, 11:30 a.m.