Triple

T22658182
Position Surface form Disambiguated ID Type / Status
Subject رشدي أباظة E559286 entity
Predicate workedWith P398 FINISHED
Object فاتن حمامة 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: فاتن حمامة | Statement: [رشدي أباظة, workedWith, فاتن حمامة]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: فاتن حمامة
Context triple: [رشدي أباظة, workedWith, فاتن حمامة]
  • A. فاتن حمامة chosen
    فاتن حمامة هي ممثلة مصرية شهيرة لُقبت بـ"سيدة الشاشة العربية" وتُعد من أبرز نجمات السينما في العالم العربي في القرن العشرين.
  • B. Hani Toukan
    Hani Toukan is a notable member of the prominent Toukan family, recognized for his public profile and contributions associated with this influential lineage.
  • C. Fathia
    Fathia was an Egyptian-born teacher and the First Lady of Ghana as the wife of its first president, Kwame Nkrumah.
  • D. Haya Harareet
    Haya Harareet was an Israeli actress best known for her role as Esther opposite Charlton Heston in the 1959 epic film "Ben-Hur."
  • E. Abla Kamel
    Abla Kamel is a renowned Egyptian actress known for her powerful performances in film, television, and theater, often portraying strong, emotionally complex women.
  • 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_69e245489dd88190b1f674acf61c8769 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1765d10588190b4574f3e64617cd4 completed April 29, 2026, 3:09 a.m.
Created at: April 17, 2026, 3:07 p.m.