Triple

T16147415
Position Surface form Disambiguated ID Type / Status
Subject Ken Biller E391820 entity
Predicate workOn P30363 FINISHED
Object Houdini E771673 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: Houdini | Statement: [Ken Biller, workOn, Houdini]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Houdini
Context triple: [Ken Biller, workOn, Houdini]
  • A. Houdini
    Houdini is most famously Harry Houdini, the early 20th-century illusionist and escape artist renowned for his daring stunts and seemingly impossible escapes.
  • B. Houdini chosen
    Houdini is a powerful commercial chess engine renowned for its creative attacking style and strong performance in top computer chess competitions.
  • C. Houdini's Great Escape
    Houdini's Great Escape is a haunted-house–themed illusion ride at Six Flags Great Adventure that combines theatrical effects with motion-simulation to create a disorienting escape-room experience.
  • D. Golem
    Golem is a classic 1915 science fiction novel by Polish writer Gustav Meyrink that reimagines the Jewish legend of a mystical clay creature brought to life in the Prague ghetto.
  • E. Blixem
    Blixem is an alternative name for Blitzen, one of Santa Claus’s traditional flying reindeer known from the Christmas poem “A Visit from St. Nicholas.”
  • 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_69d87f1c65e48190aa2b4c472e9bafc4 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21d947e68819081b4b7c757ce71b6 completed April 17, 2026, 11:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff7a7dc3481909f933acd72d6feff completed May 10, 2026, 3:12 a.m.
Created at: April 10, 2026, 5:01 a.m.