Triple

T12533284
Position Surface form Disambiguated ID Type / Status
Subject Wayne McGregor E299622 entity
Predicate hasCollaboratedWith P8554 FINISHED
Object Max Richter E619803 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: Max Richter | Statement: [Wayne McGregor, hasCollaboratedWith, Max Richter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Max Richter
Context triple: [Wayne McGregor, hasCollaboratedWith, Max Richter]
  • A. Max Richter chosen
    Max Richter is a German-British composer known for his influential contemporary classical and minimalist film scores and solo works.
  • B. Owen Pallett
    Owen Pallett is a Canadian composer, violinist, and singer-songwriter known for his intricate orchestral pop arrangements and collaborations with numerous indie rock artists.
  • C. Jóhann Jóhannsson
    Jóhann Jóhannsson was an Icelandic composer and musician renowned for his atmospheric, minimalist film scores and experimental solo works.
  • D. Yann Tiersen
    Yann Tiersen is a French musician and composer best known internationally for his whimsical, minimalist score to the film "Amélie."
  • E. Daniel Lopatin
    Daniel Lopatin is an American electronic musician and producer, best known for his work as Oneohtrix Point Never and his experimental film scores.
  • 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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9546b8fd48190ae90e80785b2e2d1 completed April 10, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64bc9b9ec8190a25e2658d79836bc completed May 2, 2026, 7:08 p.m.
Created at: April 8, 2026, 9:57 p.m.