Triple

T18825052
Position Surface form Disambiguated ID Type / Status
Subject The Heir Apparent: Largo Winch E460362 entity
Predicate starring P1507 FINISHED
Object Gilbert Melki 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: Gilbert Melki | Statement: [The Heir Apparent: Largo Winch, starring, Gilbert Melki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gilbert Melki
Context triple: [The Heir Apparent: Largo Winch, starring, Gilbert Melki]
  • A. Gilbert Melki chosen
    Gilbert Melki is a French actor known for his versatile performances in film and television, including prominent roles in French dramas and comedies.
  • B. Emile Ghantous
    Emile Ghantous is a music producer and songwriter known for his work in contemporary R&B and pop with various mainstream artists.
  • C. Antoine Nahas
    Antoine Nahas was a Lebanese architect best known for designing the National Museum of Beirut, a landmark institution of Lebanon’s cultural heritage.
  • D. Gilbert Chagoury
    Gilbert Chagoury is a Nigerian-Lebanese billionaire businessman and philanthropist known for his influential role in West African commerce and politics.
  • E. Henry Barakat
    Henry Barakat was a prominent Egyptian film director and one of the leading figures of classical Egyptian cinema.
  • 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_69d8dcf94c288190a06dea029ae4b223 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5a6bdefac8190892d6fd5c20a431e completed April 20, 2026, 4:08 a.m.
Created at: April 10, 2026, 11:56 a.m.