Triple

T14195909
Position Surface form Disambiguated ID Type / Status
Subject Jason Schwartzman E351833 entity
Predicate notableWork P4 FINISHED
Object Rushmore E77920 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: Rushmore | Statement: [Jason Schwartzman, notableWork, Rushmore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rushmore
Context triple: [Jason Schwartzman, notableWork, Rushmore]
  • A. Rushmore chosen
    Rushmore is a 1998 Wes Anderson coming-of-age comedy film starring Jason Schwartzman and Bill Murray, known for its offbeat humor, distinctive visual style, and deadpan performances.
  • B. Hancock
    Hancock is a small city in Michigan’s Upper Peninsula known for its Finnish-American heritage and proximity to Lake Superior.
  • C. Hancock
    Hancock is a prominent surname most famously associated with John Hancock, a key figure of the American Revolution and first signer of the United States Declaration of Independence.
  • D. Hancock
    Hancock is a small rural town in western Massachusetts known for its scenic Berkshire landscapes and outdoor recreation.
  • E. Sra. Rushmore
    Sra. Rushmore is a prominent Spanish advertising agency known for creating high-profile, emotionally driven campaigns for major global brands.
  • 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_69d827894ac0819097803e57f3227b23 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61e1fbd48190a4864fa4443f8f29 completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd194b32d88190aa74eef576152db3 completed May 7, 2026, 10:59 p.m.
Created at: April 10, 2026, 1:04 a.m.