Triple

T10340494
Position Surface form Disambiguated ID Type / Status
Subject PCA E243114 entity
Predicate alsoKnownAs P39 FINISHED
Object Production Code office E48473 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: Production Code office | Statement: [PCA, alsoKnownAs, Production Code office]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Production Code office
Context triple: [PCA, alsoKnownAs, Production Code office]
  • A. Production Code Administration chosen
    The Production Code Administration was the Hollywood industry office that enforced the Motion Picture Production Code, reviewing and approving film content for moral acceptability from the 1930s to the 1960s.
  • B. CODEPU
    CODEPU is a prominent Chilean human rights organization that played a key role in documenting and denouncing abuses committed during Augusto Pinochet’s military dictatorship.
  • C. The Code
    The Code is a film featuring Australian actress Kate Beahan, known for her roles in both Australian cinema and international productions.
  • D. The Code
    "The Code" is a poem by Robert Frost featured in his collection *North of Boston*, reflecting his characteristic exploration of rural New England life and moral complexity.
  • E. Source Code
    "Source Code" is a 2011 science-fiction thriller film about a soldier who repeatedly relives the last minutes of a train bombing to identify the attacker.
  • 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_69d381af787481908bc401325c760a88 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e0a526a08190afe7091a0cf1f073 completed April 7, 2026, 10:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7506a07888190b91e78247e81fe57 completed April 9, 2026, 7:08 a.m.
Created at: April 6, 2026, 11:54 a.m.