Triple

T815627
Position Surface form Disambiguated ID Type / Status
Subject Algol 68 E17646 entity
Predicate hasImplementation P3697 FINISHED
Object Algol 68R E102381 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: Algol 68R | Statement: [Algol 68, hasImplementation, Algol 68R]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Algol 68R
Context triple: [Algol 68, hasImplementation, Algol 68R]
  • A. Algol 68R chosen
    Algol 68R is a revised, more practical and implementable version of the Algol 68 programming language, created to simplify and clarify the original language’s complex design.
  • B. Algol 68S
    Algol 68S is a simplified subset of the Algol 68 programming language designed to make the language easier to implement and use.
  • C. Algol 68C
    Algol 68C is a compiler implementation of the Algol 68 programming language, designed to translate its advanced structured constructs into executable machine code.
  • 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 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_69a4937bcaac8190a322524ac6f45a5a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab5157b08190b6c8f2fd455f261e completed March 1, 2026, 9:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c7103a00819087ad711a2ab99770 completed March 4, 2026, 5:45 a.m.
Created at: March 1, 2026, 7:38 p.m.