Triple

T3389342
Position Surface form Disambiguated ID Type / Status
Subject A Very English Scandal E71379 entity
Predicate composer P1361 FINISHED
Object Murray Gold E79471 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: Murray Gold | Statement: [A Very English Scandal, composer, Murray Gold]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Murray Gold
Context triple: [A Very English Scandal, composer, Murray Gold]
  • A. Murray Gold chosen
    Murray Gold is a British composer best known for his dynamic and emotive scores for the revived Doctor Who television series and its spin-offs.
  • B. 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.
  • C. Ernest Gold
    Ernest Gold was an Austrian-born American composer best known for his acclaimed film scores, including the Oscar-winning music for "Exodus."
  • D. Ron Goodwin
    Ron Goodwin was a British composer and conductor best known for his rousing film scores for war and adventure movies in the mid-20th century.
  • E. Rupert Gregson-Williams
    Rupert Gregson-Williams is a British film and television composer known for scoring major Hollywood productions such as "Wonder Woman," "Aquaman," and "The Crown."
  • 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_69ad85a8fd9c819095ecedf838d2bf1b completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb666e514819090560d43bfaf55b8 completed March 8, 2026, 5:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b360aded3c8190ab4ca37b4aead1df completed March 13, 2026, 12:56 a.m.
Created at: March 8, 2026, 3:14 p.m.