Triple

T14440328
Position Surface form Disambiguated ID Type / Status
Subject Kristen Nygaard E358068 entity
Predicate knownFor P22 FINISHED
Object Simula I E72066 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: Simula I | Statement: [Kristen Nygaard, knownFor, Simula I]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Simula I
Context triple: [Kristen Nygaard, knownFor, Simula I]
  • A. Simula chosen
    Simula is an early high-level programming language from the 1960s that pioneered object-oriented programming concepts such as classes and objects.
  • B. Algol 68 Genie
    Algol 68 Genie is a modern, open-source implementation of the Algol 68 programming language designed for contemporary systems and practical use.
  • C. Algol 68S
    Algol 68S is a simplified subset of the Algol 68 programming language designed to make the language easier to implement and use.
  • D. Algol 68
    Algol 68 is a high-level, structured programming language from the ALGOL family, notable for its orthogonal design and influence on many later languages.
  • E. Algol W
    Algol W is a block-structured, high-level programming language designed by Niklaus Wirth as a successor to ALGOL 60, incorporating features that influenced the later development of Pascal and other languages.
  • 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_69d8279402a88190821ffa39ae15bccf completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de914c1398819090fa2a74d257ba3e completed April 14, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd648d8904819084d720a0fd2ddb4b completed May 8, 2026, 4:20 a.m.
Created at: April 10, 2026, 1:18 a.m.