Triple

T22149092
Position Surface form Disambiguated ID Type / Status
Subject Dil Apna Aur Preet Parai E547366 entity
Predicate starring P1507 FINISHED
Object Nadira
Nadira was a prominent Indian film actress known for her memorable supporting and vamp roles in classic Hindi cinema from the 1950s and 1960s.
 E1521575 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: Nadira | Statement: [Dil Apna Aur Preet Parai, starring, Nadira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nadira
Context triple: [Dil Apna Aur Preet Parai, starring, Nadira]
  • A. Nandini
    Nandini is a divine cow in Hindu mythology, famed as a wish-fulfilling offspring of the celestial cow Kamadhenu.
  • B. Zeenat
    Zeenat is the given name of Zeenat Karzai, the wife of former Afghan President Hamid Karzai and a former gynecologist.
  • C. Raakhee
    Raakhee is a renowned Indian film actress known for her acclaimed performances in Hindi and Bengali cinema from the late 1960s through the 1980s.
  • D. Naseem
    Naseem is the given name of Naseem Hamed, the British former professional boxer famed for his flamboyant style and knockout power.
  • E. Naseem
    Naseem is an Indian art-house film directed by Saeed Akhtar Mirza that poignantly portrays the rising communal tensions in Bombay leading up to the Babri Masjid demolition.
  • 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: Nadira
Triple: [Dil Apna Aur Preet Parai, starring, Nadira]
Generated description
Nadira was a prominent Indian film actress known for her memorable supporting and vamp roles in classic Hindi cinema from the 1950s and 1960s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nadira
Target entity description: Nadira was a prominent Indian film actress known for her memorable supporting and vamp roles in classic Hindi cinema from the 1950s and 1960s.
  • A. Nandini
    Nandini is a divine cow in Hindu mythology, famed as a wish-fulfilling offspring of the celestial cow Kamadhenu.
  • B. Zeenat
    Zeenat is the given name of Zeenat Karzai, the wife of former Afghan President Hamid Karzai and a former gynecologist.
  • C. Raakhee
    Raakhee is a renowned Indian film actress known for her acclaimed performances in Hindi and Bengali cinema from the late 1960s through the 1980s.
  • D. Naseem
    Naseem is an Indian art-house film directed by Saeed Akhtar Mirza that poignantly portrays the rising communal tensions in Bombay leading up to the Babri Masjid demolition.
  • E. Naseem
    Naseem is the given name of Naseem Hamed, the British former professional boxer famed for his flamboyant style and knockout power.
  • 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_69e11e3b52088190ad5df386d01eb2fb completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129f2c0e881909c3488bb5eb5959d completed April 28, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a9702ed508190ac4db27c3dc46879 completed May 18, 2026, 4:35 a.m.
NEDg Description generation batch_6a0a97bd6fe081909a3e609ff2022f82 completed May 18, 2026, 4:38 a.m.
NED2 Entity disambiguation (via description) batch_6a0a9843fb3481908a120dc3ac360124 completed May 18, 2026, 4:40 a.m.
Created at: April 16, 2026, 8:33 p.m.