Triple

T14500441
Position Surface form Disambiguated ID Type / Status
Subject Lizabeth Scott E359619 entity
Predicate notableWork P4 FINISHED
Object Pitfall E82379 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: Pitfall | Statement: [Lizabeth Scott, notableWork, Pitfall]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pitfall
Context triple: [Lizabeth Scott, notableWork, Pitfall]
  • A. Pitfall chosen
    Pitfall is a 1948 American film noir crime drama directed by André De Toth, noted for its dark exploration of suburban discontent and moral compromise.
  • B. Pitfall!
    Pitfall! is a pioneering 1982 side-scrolling action-adventure video game for the Atari 2600, widely regarded as one of the earliest and most influential platformers.
  • C. Boulder Dash
    Boulder Dash is a renowned wooden roller coaster celebrated for its terrain-hugging layout through the forested hillside at Lake Compounce in Connecticut.
  • D. Super Pit
    The Super Pit is one of Australia’s largest open-cut gold mines, located on the outskirts of Kalgoorlie in Western Australia.
  • E. The Gauntlet
    The Gauntlet is a 1977 action thriller film directed by and starring Clint Eastwood as a down-and-out cop escorting a key witness through a deadly ambush-laden journey.
  • 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_69d8279740308190af9df93a3af8592e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de94dfe484819086dd971606e6478e completed April 14, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6d9b6f7481908b7eb76226a93545 completed May 8, 2026, 4:59 a.m.
Created at: April 10, 2026, 1:21 a.m.