Triple

T16527784
Position Surface form Disambiguated ID Type / Status
Subject Saeed Akhtar Mirza E401484 entity
Predicate notableWork P4 FINISHED
Object 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.
E1219852 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: Naseem | Statement: [Saeed Akhtar Mirza, notableWork, Naseem]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naseem
Context triple: [Saeed Akhtar Mirza, notableWork, Naseem]
  • A. Naseem
    Naseem is the given name of Naseem Hamed, the British former professional boxer famed for his flamboyant style and knockout power.
  • B. Najma
    Najma was the mother of Ali al-Rida, the eighth Shia Imam, and is venerated in Islamic tradition for her piety and role in his upbringing.
  • C. Shabana
    Shabana is a prominent Bangladeshi film actress renowned for her extensive and influential career in Bengali cinema.
  • D. Zeenat
    Zeenat is the given name of Zeenat Karzai, the wife of former Afghan President Hamid Karzai and a former gynecologist.
  • E. Nubeena
    Nubeena is a small coastal town on Tasmania’s Tasman Peninsula known as a local service and tourism hub for the surrounding rural and scenic areas.
  • 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: Naseem
Triple: [Saeed Akhtar Mirza, notableWork, Naseem]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Naseem
Target entity description: 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.
  • A. Naseem
    Naseem is the given name of Naseem Hamed, the British former professional boxer famed for his flamboyant style and knockout power.
  • B. Najma
    Najma was the mother of Ali al-Rida, the eighth Shia Imam, and is venerated in Islamic tradition for her piety and role in his upbringing.
  • C. Shabana
    Shabana is a prominent Bangladeshi film actress renowned for her extensive and influential career in Bengali cinema.
  • D. Zeenat
    Zeenat is the given name of Zeenat Karzai, the wife of former Afghan President Hamid Karzai and a former gynecologist.
  • E. Nubeena
    Nubeena is a small coastal town on Tasmania’s Tasman Peninsula known as a local service and tourism hub for the surrounding rural and scenic areas.
  • 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_69d883838abc8190bc79cb2d41733ce2 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32ed4b8a08190b5f179fc583001a6 completed April 18, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0067a7616c8190af486bef3331e115 completed May 10, 2026, 11:10 a.m.
NEDg Description generation batch_6a006914e0588190afdd0e7c2719696f completed May 10, 2026, 11:16 a.m.
NED2 Entity disambiguation (via description) batch_6a00696d42e081908133fdbee4a301d8 completed May 10, 2026, 11:18 a.m.
Created at: April 10, 2026, 5:14 a.m.