Triple

T20592945
Position Surface form Disambiguated ID Type / Status
Subject Margit Saad E505976 entity
Predicate name P16 FINISHED
Object Margit Saad 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: Margit Saad | Statement: [Margit Saad, name, Margit Saad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margit Saad
Context triple: [Margit Saad, name, Margit Saad]
  • A. Margit Saad chosen
    Margit Saad was a German actress known for her film and television work in the 1950s and 1960s, often appearing in European and British productions.
  • B. Margot Al-Harazi
    Margot Al-Harazi is a primary antagonist in the television event series "24: Live Another Day," depicted as a ruthless terrorist leader orchestrating large-scale attacks against London.
  • C. Aida El-Kachef
    Aida El-Kachef is known as the wife of Egyptian diplomat and Nobel Peace Prize laureate Mohamed ElBaradei.
  • D. Mizzi Ahmar
    Mizzi Ahmar is a reddish variety of Jerusalem stone commonly used as a traditional building material in and around Jerusalem.
  • E. Mary Lib Saleh
    Mary Lib Saleh was a prominent local figure and community advocate in Euless, Texas, honored for her contributions by having the city’s public library named after her.
  • 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_69e0b4ba6ae88190af871e1f9522c704 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a97d63cc8190853e052d5930470d completed April 20, 2026, 10:32 p.m.
Created at: April 16, 2026, 11:40 a.m.