Triple

T3418669
Position Surface form Disambiguated ID Type / Status
Subject Simula E72066 entity
Predicate standardizedAs P1371 FINISHED
Object Simula 67 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 67 | Statement: [Simula, standardizedAs, Simula 67]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Simula 67
Context triple: [Simula, standardizedAs, Simula 67]
  • 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
    Algol 68 is a high-level, structured programming language from the ALGOL family, notable for its orthogonal design and influence on many later languages.
  • C. 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.
  • D. Algol 68S
    Algol 68S is a simplified subset of the Algol 68 programming language designed to make the language easier to implement and use.
  • E. ALGOL 60
    ALGOL 60 is an early high-level programming language that pioneered block structure and lexical scoping, profoundly influencing the design of many later 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_69ad85ad38e48190b7660c5118a35289 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb92df1e48190bbf22a47e44579f1 completed March 8, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69b360c285688190a264fcb4ab271b82 completed March 13, 2026, 12:56 a.m.
Created at: March 8, 2026, 3:15 p.m.