Triple

T1191278
Position Surface form Disambiguated ID Type / Status
Subject Bert Bos E25365 entity
Predicate name P16 FINISHED
Object Bert Bos E25365 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: Bert Bos | Statement: [Bert Bos, name, Bert Bos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bert Bos
Context triple: [Bert Bos, name, Bert Bos]
  • A. Bert Bos chosen
    Bert Bos is a Dutch computer scientist best known as a co-creator and long-time editor of the CSS (Cascading Style Sheets) web standard.
  • B. Bert Koenders
    Bert Koenders is a Dutch Labour Party politician and diplomat who served as the Netherlands’ Minister of Foreign Affairs and previously held roles including Minister for Development Cooperation and UN Special Representative.
  • C. Hubert Bruls
    Hubert Bruls is a Dutch politician best known as the long-serving mayor of Nijmegen and a prominent figure in national public safety and crisis management.
  • D. Jan van der Linden
    Jan van der Linden was an architect known for his role in designing Los Angeles’ historic Union Station.
  • E. Andries van Dam
    Andries van Dam is a pioneering computer scientist best known for his foundational work in computer graphics and hypertext systems, and for co-authoring one of the earliest and most influential computer graphics textbooks.
  • 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_69a49427d98881908646d6c63b8cea1e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd74e2c08190b4a48425f94addaa completed March 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac764ea588819082f7d5d0e44e1211 completed March 7, 2026, 7:02 p.m.
Created at: March 1, 2026, 7:45 p.m.