Triple

T14398295
Position Surface form Disambiguated ID Type / Status
Subject Sliver E357006 entity
Predicate musicBy P1952 FINISHED
Object Howard Shore E39854 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: Howard Shore | Statement: [Sliver, musicBy, Howard Shore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Howard Shore
Context triple: [Sliver, musicBy, Howard Shore]
  • A. Howard Shore chosen
    Howard Shore is a Canadian composer and conductor best known for his acclaimed film scores, including the music for The Lord of the Rings trilogy.
  • B. James Horner
    James Horner was an Academy Award–winning American film composer renowned for his emotionally powerful scores for movies such as Titanic, Braveheart, and A Beautiful Mind.
  • C. Harry Gregson-Williams
    Harry Gregson-Williams is a British composer best known for his film and video game scores, including work on the "Shrek" series, "The Chronicles of Narnia," and the "Metal Gear Solid" franchise.
  • D. John Williams
    John Williams is an acclaimed American composer and conductor best known for his iconic film scores for franchises such as Star Wars, Indiana Jones, Harry Potter, and many others.
  • E. John Williams
    John Williams was a British actor known for his character roles in mid-20th-century films and television, including classic courtroom dramas and comedies.
  • 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_69d827927c988190ad98bb0360981783 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de9083f9d081908fe5c99655c410b3 completed April 14, 2026, 7:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd551eb09c8190a102ab452371e5b1 completed May 8, 2026, 3:14 a.m.
Created at: April 10, 2026, 1:17 a.m.