Triple

T2314101
Position Surface form Disambiguated ID Type / Status
Subject Lambert Meertens E51022 entity
Predicate notableStudent P4838 FINISHED
Object Guido van Rossum E1899 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: Guido van Rossum | Statement: [Lambert Meertens, notableStudent, Guido van Rossum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guido van Rossum
Context triple: [Lambert Meertens, notableStudent, Guido van Rossum]
  • A. Guido van Rossum chosen
    Guido van Rossum is a Dutch programmer best known as the creator of the Python programming language.
  • B. Robert Kern
    Robert Kern was an American film editor active during Hollywood’s classic studio era, known for his work on numerous prominent MGM productions.
  • C. Larry Wall
    Larry Wall is an American programmer and linguist best known as the creator of the Perl programming language and a prominent figure in the free and open-source software community.
  • D. Linus Torvalds
    Linus Torvalds is a Finnish-American software engineer best known as the creator and principal developer of the Linux kernel, the core of the widely used Linux operating system.
  • E. Yukihiro Matsumoto
    Yukihiro Matsumoto is a Japanese software engineer best known as the creator of the Ruby programming language and a prominent figure in the free software community.
  • 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_69a88b074b908190ae983dbca7757d88 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc61c1ef08190911d5f58c2e91189 completed March 7, 2026, 6:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69aea87427f08190b8353f74c5231a32 completed March 9, 2026, 11:01 a.m.
Created at: March 4, 2026, 7:49 p.m.