Triple

T5224593
Position Surface form Disambiguated ID Type / Status
Subject Rawhide E117953 entity
Predicate musicBy P1952 FINISHED
Object Sol Kaplan E504336 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: Sol Kaplan | Statement: [Rawhide, musicBy, Sol Kaplan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sol Kaplan
Context triple: [Rawhide, musicBy, Sol Kaplan]
  • A. Sol Kaplan chosen
    Sol Kaplan was an American composer best known for his film and television scores, including work in mid-20th-century Hollywood.
  • B. Greg Kaplan
    Greg Kaplan is an economist known for his research on household heterogeneity, consumption, and macroeconomic policy, and for his contributions to modern macroeconomic modeling.
  • C. Larry Kaplan
    Larry Kaplan is a pioneering video game designer and programmer best known as one of the co-founders of Activision and an early developer for the Atari 2600.
  • D. Jonathan Kaplan
    Jonathan Kaplan is an American film and television director best known for his work on the acclaimed 1988 courtroom drama "The Accused."
  • E. Mitch Kertzman
    Mitch Kertzman is an American technology executive and entrepreneur best known for his leadership roles in the software and semiconductor industries, including at companies like LSI Logic and Sybase.
  • 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_69bd4465e03081909bfcfd7113062590 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7abd3ed48190bfd8d2f2ca399741 completed March 20, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf331e0e2881908b52da110384302a completed March 22, 2026, 12:09 a.m.
Created at: March 20, 2026, 1:48 p.m.