Triple

T22233000
Position Surface form Disambiguated ID Type / Status
Subject Christian Kroll E549515 entity
Predicate employer P7 FINISHED
Object Ecosia NE NERFINISHED

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: Ecosia | Statement: [Christian Kroll, employer, Ecosia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ecosia
Context triple: [Christian Kroll, employer, Ecosia]
  • A. Ecosia chosen
    Ecosia is a privacy-focused search engine that uses its ad revenue to fund tree-planting and reforestation projects around the world.
  • B. Brave Search
    Brave Search is a privacy-focused, independent search engine developed by Brave that emphasizes user anonymity and reduced tracking.
  • C. Qwant
    Qwant is a French privacy-focused search engine that emphasizes user anonymity and does not track or profile its users.
  • D. GoodPlanet Foundation
    GoodPlanet Foundation is a French non-profit organization dedicated to environmental protection, sustainability education, and promoting ecological awareness worldwide.
  • E. Goole
    Goole is an inland port town in the East Riding of Yorkshire, England, known for its significant docks and role in regional maritime trade.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e4102b881909cf47d3768e25c19 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12bf4e0348190b755a9ac0bc96cdd completed April 28, 2026, 9:51 p.m.
Created at: April 16, 2026, 8:38 p.m.