Triple

T22982075
Position Surface form Disambiguated ID Type / Status
Subject Abdel Halim Hafez E571495 entity
Predicate familyName P18 FINISHED
Object Shabana 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: Shabana | Statement: [Abdel Halim Hafez, familyName, Shabana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shabana
Context triple: [Abdel Halim Hafez, familyName, Shabana]
  • A. Shabana chosen
    Shabana is a prominent Bangladeshi film actress renowned for her extensive and influential career in Bengali cinema.
  • B. Tirana Hassan
    Tirana Hassan is a human rights lawyer and advocate who serves as the executive director of Human Rights Watch, leading global efforts to investigate and expose human rights abuses.
  • C. Shibani Bathija
    Shibani Bathija is an Indian screenwriter best known for writing popular Bollywood films such as "Fanaa" and "Kabhi Alvida Naa Kehna."
  • D. Shahnaz
    Shahnaz is an Iranian princess and the eldest child of Mohammad Reza Pahlavi, the last Shah of Iran.
  • E. Shahnaz Lalarukh
    Shahnaz Lalarukh is the elder sister of Bollywood actor Shah Rukh Khan, known for maintaining a very private life away from the film industry.
  • 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_69e245b3c50481908bb3741ec9f40862 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1829645f88190aea1b96ea595ff60 completed April 29, 2026, 4:01 a.m.
Created at: April 17, 2026, 3:49 p.m.