Triple

T17799885
Position Surface form Disambiguated ID Type / Status
Subject Rose Loomis E444392 entity
Predicate partOf P40 FINISHED
Object Niagara (1953 film) NE NERFINISHED

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: Niagara (1953 film) | Statement: [Rose Loomis, partOf, Niagara (1953 film)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Niagara (1953 film)
Context triple: [Rose Loomis, partOf, Niagara (1953 film)]
  • A. Niagara (1953 film) chosen
    Niagara (1953 film) is a 1953 American film noir thriller starring Marilyn Monroe, notable for its suspenseful plot set around a honeymooning couple at Niagara Falls.
  • B. Niagara, Niagara
    "Niagara, Niagara" is a 1997 independent road drama film following two troubled teenagers on a chaotic journey across the American Northeast.
  • C. "Niagara"
    "Niagara" is a popular two-part episode of the U.S. version of The Office centered on Jim and Pam’s wedding at Niagara Falls.
  • D. Niagara 2
    Niagara 2 is the code name for Sun Microsystems' UltraSPARC T2 multicore, multithreaded server processor designed for high-throughput computing.
  • E. Coney Island (1943 film)
    Coney Island (1943 film) is a Technicolor musical starring Betty Grable that nostalgically portrays turn-of-the-century entertainment culture at New York’s famous amusement destination.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9efe370819095cd219b143ae727 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e487fe19dc8190b7e9dc96f39e0861 completed April 19, 2026, 7:45 a.m.
Created at: April 10, 2026, 10:13 a.m.