Triple

T16331470
Position Surface form Disambiguated ID Type / Status
Subject Trapped in the Flames E396563 entity
Predicate hasMainStar P24826 FINISHED
Object Bela Lugosi E116562 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: Bela Lugosi | Statement: [Trapped in the Flames, hasMainStar, Bela Lugosi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bela Lugosi
Context triple: [Trapped in the Flames, hasMainStar, Bela Lugosi]
  • A. Bela Lugosi chosen
    Bela Lugosi was a Hungarian-American actor best known for his iconic portrayal of Count Dracula in early horror cinema.
  • B. Bela Lugosi Jr.
    Bela Lugosi Jr. is an American attorney and the son of legendary horror film actor Bela Lugosi, known for his legal work related to his father's legacy and likeness rights.
  • C. 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."
  • D. Lillian Arch Lugosi
    Lillian Arch Lugosi was the wife of actor Brian Donlevy and is primarily known for her marriage to him.
  • E. Vincent Price
    Vincent Price was an American actor renowned for his distinctive voice and charismatic presence, particularly in classic horror films and gothic dramas.
  • 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_69d87f255b788190a400eba031dd85d8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2c4dfd9688190a749e48ebc055baf completed April 17, 2026, 11:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a007d9a8d7481908c7bc4711ddacc13 completed May 10, 2026, 12:44 p.m.
Created at: April 10, 2026, 5:07 a.m.