Triple

T15078079
Position Surface form Disambiguated ID Type / Status
Subject Suzan Farmer E380058 entity
Predicate associatedWith P37 FINISHED
Object Boris Karloff E218089 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: Boris Karloff | Statement: [Suzan Farmer, associatedWith, Boris Karloff]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Boris Karloff
Context triple: [Suzan Farmer, associatedWith, Boris Karloff]
  • A. Boris Karloff chosen
    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."
  • B. Bela Lugosi
    Bela Lugosi was a Hungarian-American actor best known for his iconic portrayal of Count Dracula in early horror cinema.
  • C. Vincent Price
    Vincent Price was an American actor renowned for his distinctive voice and charismatic presence, particularly in classic horror films and gothic dramas.
  • D. Vincent E. Price
    Vincent E. Price is an American political communication scholar and academic leader who serves as the president of Duke University.
  • E. Sara Karloff
    Sara Karloff is an American producer and public figure best known for preserving and promoting the legacy of her father, classic horror film icon Boris Karloff.
  • 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_69d85cd7683881908d405c1b5d7b4f7f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69dff7fe5a208190823900b25e298dab completed April 15, 2026, 8:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69fea5d4f6a48190aeb42341b0c395a7 completed May 9, 2026, 3:11 a.m.
Created at: April 10, 2026, 3:03 a.m.