Triple

T400628
Position Surface form Disambiguated ID Type / Status
Subject NLUUG Award E9271 entity
Predicate notableRecipient P108 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: [NLUUG Award, notableRecipient, Guido van Rossum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guido van Rossum
Context triple: [NLUUG Award, notableRecipient, 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. 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.
  • C. 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.
  • D. 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.
  • E. Tony Hoare
    Tony Hoare is a British computer scientist best known for developing the Quicksort algorithm and making foundational contributions to programming languages and formal methods.
  • 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_69a2e8004cb88190b92ed1add6abf41a completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ec8e655c819081eff85c0ef55fa5 completed Feb. 28, 2026, 1:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69a41772e19c8190b02a212f13b4d8aa completed March 1, 2026, 10:39 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.