Triple

T13960131
Position Surface form Disambiguated ID Type / Status
Subject Delft city views E335769 entity
Predicate notableArtist P601 FINISHED
Object Egbert van der Poel E67159 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: Egbert van der Poel | Statement: [Delft city views, notableArtist, Egbert van der Poel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Egbert van der Poel
Context triple: [Delft city views, notableArtist, Egbert van der Poel]
  • A. Egbert van der Poel chosen
    Egbert van der Poel was a 17th-century Dutch Golden Age painter known for his atmospheric depictions of fires, nocturnal scenes, and everyday life in and around Delft.
  • B. Daan Wierstra
    Daan Wierstra is a machine learning researcher known for his contributions to deep reinforcement learning, including co-authoring the influential Atari deep Q-network work at DeepMind.
  • C. Maarten Baas
    Maarten Baas is a Dutch designer and artist renowned for his conceptual, often playful furniture and installations that blur the boundaries between art and design.
  • D. Marc de Jonge
    Marc de Jonge was a French actor best known internationally for playing the Soviet Colonel Zaysen in the action film "Rambo III."
  • E. Bart van Merriënboer
    Bart van Merriënboer is a machine learning researcher known for his contributions to deep learning and neural sequence models, including work on RNN-based encoder–decoder architectures for machine translation.
  • 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_69d81c61f3508190aaf2ca0dc0002c59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e7b2f908190aa32f22298964746 completed April 14, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdef3f31c8190a2fc3eed316756d6 completed May 7, 2026, 6:50 p.m.
Created at: April 9, 2026, 10:17 p.m.