Triple

T14702337
Position Surface form Disambiguated ID Type / Status
Subject Steven E. de Souza E345336 entity
Predicate notableWork P4 FINISHED
Object Ricochet E371109 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: Ricochet | Statement: [Steven E. de Souza, notableWork, Ricochet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ricochet
Context triple: [Steven E. de Souza, notableWork, Ricochet]
  • A. Ricochet chosen
    Ricochet is a 1991 action thriller film in which John Lithgow plays a sadistic criminal seeking revenge on a cop who put him behind bars.
  • B. Ricochet
    Ricochet is a wild mouse–style steel roller coaster known for its sharp turns and sudden drops at the Carowinds amusement park.
  • C. Ricochet
    Ricochet was an early wireless internet service network developed by Metricom that provided mobile, high-speed data access in urban areas before Wi-Fi and modern cellular data became widespread.
  • D. "Ricochet"
    "Ricochet" is a popular 1953 novelty pop song performed by American singer Teresa Brewer.
  • E. Bounce
    "Bounce" is a popular electro house track by Canadian electronic music duo MSTRKRFT, known for its heavy synths and club-oriented energy.
  • 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_69d822e4a8c08190a155df736bb7bc13 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb6071e5c8190bb5509c859135c2d completed April 14, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf0861c308190af0b5da403ecb321 completed May 8, 2026, 2:17 p.m.
Created at: April 10, 2026, 1:28 a.m.