Triple

T9397033
Position Surface form Disambiguated ID Type / Status
Subject Shadow of the Vampire E226168 entity
Predicate characterIn P12208 FINISHED
Object Max Schreck E796869 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: Max Schreck | Statement: [Shadow of the Vampire, characterIn, Max Schreck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Max Schreck
Context triple: [Shadow of the Vampire, characterIn, Max Schreck]
  • A. Max Schreck chosen
    Max Schreck was a German actor best known for his iconic and eerie portrayal of the vampire Count Orlok in the 1922 silent horror film "Nosferatu."
  • B. Bela Lugosi
    Bela Lugosi was a Hungarian-American actor best known for his iconic portrayal of Count Dracula in early horror cinema.
  • C. Tod Browning
    Tod Browning was an American film director best known for his influential early horror films, including "Dracula" (1931) and "Freaks" (1932).
  • D. Wilhelm Speidel
    Wilhelm Speidel was a German Luftwaffe general during World War II who was later tried and convicted for war crimes committed in occupied Greece.
  • E. Boris Karloff
    Boris Karloff was an English actor best known for his iconic portrayals in classic horror films, particularly as Frankenstein's monster in the 1931 film "Frankenstein."
  • 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_69ca842f7e3481908bf5bcf52e032dbd completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd51528b2481908ca1f1840d2594b4 completed April 1, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69d107949fe4819089f68a2c368af82f completed April 4, 2026, 12:44 p.m.
Created at: March 30, 2026, 7:46 p.m.