Triple

T6383923
Position Surface form Disambiguated ID Type / Status
Subject The Ocean Cleanup E143651 entity
Predicate foundedBy P104 FINISHED
Object Boyan Slat E143651 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: Boyan Slat | Statement: [The Ocean Cleanup, foundedBy, Boyan Slat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Boyan Slat
Context triple: [The Ocean Cleanup, foundedBy, Boyan Slat]
  • A. Boyan Slat chosen
    Boyan Slat is a Dutch inventor and environmental entrepreneur best known as the founder and CEO of The Ocean Cleanup, a project developing technologies to remove plastic pollution from the world’s oceans and rivers.
  • B. Tim Smit
    Tim Smit is a Dutch-born British businessman and conservationist best known as the co-founder and driving force behind Cornwall’s Eden Project.
  • C. Boyan
    Boyan is a male given name used in various Slavic countries, notably borne by environmental entrepreneur Boyan Slat.
  • D. Daniel Ganz
    Daniel Ganz is the son of acclaimed Swiss actor Bruno Ganz.
  • E. Jonas Schneider
    Jonas Schneider is a researcher in reinforcement learning best known for co-authoring the Hindsight Experience Replay technique for more efficient learning from sparse rewards.
  • 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_69c008dac1ec81909cef8157ccd69962 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06856434481909cbbca1c12c6e070 completed March 22, 2026, 10:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69c640b7e89881908e1c39d45e8a8473 completed March 27, 2026, 8:32 a.m.
Created at: March 22, 2026, 4:34 p.m.