Triple

T20179740
Position Surface form Disambiguated ID Type / Status
Subject The Golden King: The World of Tutankhamun E492693 entity
Predicate mainSubject P3 FINISHED
Object Tutankhamun 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: Tutankhamun | Statement: [The Golden King: The World of Tutankhamun, mainSubject, Tutankhamun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tutankhamun
Context triple: [The Golden King: The World of Tutankhamun, mainSubject, Tutankhamun]
  • A. Tutankhamun chosen
    Tutankhamun was a young 18th-dynasty Egyptian pharaoh whose nearly intact tomb, discovered in 1922, made him one of the most famous figures of ancient Egypt.
  • B. Kahmunrah
    Kahmunrah is the power-hungry ancient Egyptian pharaoh and main antagonist in the film "Night at the Museum: Battle of the Smithsonian."
  • C. Neferkare
    Neferkare is the throne name of the ancient Egyptian pharaoh Pepi II, a long-reigning ruler of the Sixth Dynasty in the Old Kingdom.
  • D. Ramerrez
    Ramerrez is the bandit-hero and romantic lead of Puccini’s opera *La fanciulla del West*, whose love for the saloon owner Minnie drives the drama.
  • E. Thutmose
    Thutmose was an ancient Egyptian sculptor of the 14th century BCE, best known for creating the iconic bust of Queen Nefertiti.
  • 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_69da6268a034819081cbd9ea5a1c9475 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e668edf27881909820f9103e72533e completed April 20, 2026, 5:57 p.m.
Created at: April 11, 2026, 11:36 p.m.