Triple

T3484146
Position Surface form Disambiguated ID Type / Status
Subject Pork Chop Hill (1959 film) E73566 entity
Predicate editedBy P1954 FINISHED
Object Frederic Knudtson E238104 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: Frederic Knudtson | Statement: [Pork Chop Hill (1959 film), editedBy, Frederic Knudtson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frederic Knudtson
Context triple: [Pork Chop Hill (1959 film), editedBy, Frederic Knudtson]
  • A. Frederic Knudtson chosen
    Frederic Knudtson was an American film editor known for his work on numerous Hollywood productions in the mid-20th century.
  • B. Sten Carl Bielke
    Sten Carl Bielke was an 18th-century Swedish statesman and scientist who played a key role in advancing scientific institutions in Sweden.
  • C. Gustav Gull
    Gustav Gull was a prominent Swiss architect best known for his influential public buildings in Zurich around the turn of the 20th century.
  • D. Georg C. F. Greve
    Georg C. F. Greve is a German physicist and software developer best known as a leading advocate for free software and the founding president of the Free Software Foundation Europe.
  • E. William Tunberg
    William Tunberg was an American screenwriter best known for adapting the classic 1957 Disney film "Old Yeller."
  • 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_69ad85b3c9b08190857cae74c7f36da9 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbb795db88190805b26d9774fdb73 completed March 8, 2026, 6:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69b373b5086081908ee4491860597557 completed March 13, 2026, 2:17 a.m.
Created at: March 8, 2026, 3:17 p.m.