Triple

T15678499
Position Surface form Disambiguated ID Type / Status
Subject The Seventh Sin E377507 entity
Predicate screenwriter P2831 FINISHED
Object Karl Tunberg E288330 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: Karl Tunberg | Statement: [The Seventh Sin, screenwriter, Karl Tunberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karl Tunberg
Context triple: [The Seventh Sin, screenwriter, Karl Tunberg]
  • A. Karl Tunberg chosen
    Karl Tunberg was an American screenwriter best known for writing the screenplay of the epic 1959 film "Ben-Hur."
  • B. William Tunberg
    William Tunberg was an American screenwriter best known for adapting the classic 1957 Disney film "Old Yeller."
  • C. Carl Kjeldsberg
    Carl Kjeldsberg is a pathologist and academic leader best known as a co-founder of ARUP Laboratories, a major national clinical and anatomic pathology reference laboratory.
  • D. Karl Engemann
    Karl Engemann is an American music industry executive and talent manager best known for his long association with the Osmond family and other entertainment clients.
  • E. Karl Sodersten
    Karl Sodersten is a film editor known for his work on the Australian psychological thriller "Lantana."
  • 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_69d85cd2e28481909d4e975bee20872f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f2f1640819086efd5a73bb9734a completed April 16, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ee0446881909e9c2504d51d49a3 completed May 9, 2026, 5:29 p.m.
Created at: April 10, 2026, 4:16 a.m.