Triple

T4070250
Position Surface form Disambiguated ID Type / Status
Subject Armin van Buuren E86628 entity
Predicate birthName P65 FINISHED
Object Armin Jozef Jacobus Daniël van Buuren E86628 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: Armin Jozef Jacobus Daniël van Buuren | Statement: [Armin van Buuren, birthName, Armin Jozef Jacobus Daniël van Buuren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Armin Jozef Jacobus Daniël van Buuren
Context triple: [Armin van Buuren, birthName, Armin Jozef Jacobus Daniël van Buuren]
  • A. Armin van Buuren chosen
    Armin van Buuren is a Dutch DJ, record producer, and radio show host widely recognized as one of the leading figures in trance and electronic dance music.
  • B. Leo Beenhakker
    Leo Beenhakker is a Dutch football manager renowned for coaching top clubs and national teams, including Real Madrid, Ajax, and the Netherlands.
  • C. Sebastian Tapijn
    Sebastian Tapijn was a military commander known for leading the defense of Maastricht during the Eighty Years' War.
  • D. Joost Lips
    Joost Lips was a Flemish humanist and classical scholar of the late Renaissance, renowned for his influential works on Stoic philosophy and Roman history.
  • E. Aaron van den Oord
    Aaron van den Oord is a machine learning researcher known for leading the development of WaveNet and other influential deep generative models for audio and representation learning.
  • 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_69aed93ebe448190a1f1686e28740ac9 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefc1f6d9c8190845d2fcd15fcdfd6 completed March 9, 2026, 4:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69b562b6eb708190a7f60192d8df9a27 completed March 14, 2026, 1:29 p.m.
Created at: March 9, 2026, 3:38 p.m.