Triple

T2701002
Position Surface form Disambiguated ID Type / Status
Subject Styles P E59226 entity
Predicate notableWork P4 FINISHED
Object Phantom and the Ghost E290734 NE FINISHED

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: Phantom and the Ghost | Statement: [Styles P, notableWork, Phantom and the Ghost]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Phantom and the Ghost
Context triple: [Styles P, notableWork, Phantom and the Ghost]
  • A. The Ghost
    The Ghost is the spectral apparition of Hamlet’s deceased father in Shakespeare’s tragedy, whose revelations set the play’s revenge plot in motion.
  • B. The Ghost chosen
    The Ghost is the stage name of Styles P, an American rapper known for his work with The LOX and D-Block Records.
  • C. The Phantom Creeps
    The Phantom Creeps is a 1939 science-fiction movie serial featuring Bela Lugosi as a mad scientist who unleashes deadly inventions in a bid for world domination.
  • D. Phantom
    Phantom is a hostile flying undead mob in Minecraft that swoops down from the night sky to attack players who haven’t slept for several days.
  • E. The Ghost and the Darkness
    The Ghost and the Darkness is a 1996 historical thriller film dramatizing the true story of two man-eating lions that terrorized railway workers in Tsavo, Kenya, in the late 19th century.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ab4ac66bc88190b9e4afa5fc843f72 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abda4c8d34819094f5e4cbc5a4bb9b completed March 7, 2026, 7:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69afb68060288190b03e024048b78a33 completed March 10, 2026, 6:13 a.m.
Created at: March 6, 2026, 9:55 p.m.