Triple

T1892246
Position Surface form Disambiguated ID Type / Status
Subject IBM RS/6000 E41897 entity
Predicate supportsProgrammingLanguage P1592 FINISHED
Object Fortran E59594 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: Fortran | Statement: [IBM RS/6000, supportsProgrammingLanguage, Fortran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fortran
Context triple: [IBM RS/6000, supportsProgrammingLanguage, Fortran]
  • A. Fortran chosen
    Fortran is a high-level programming language, particularly strong in numerical and scientific computing, widely used for engineering, physics, and high-performance applications.
  • B. 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.
  • 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 68R
    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.
  • 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_69a8864b6de0819098d089f6a1b910a7 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb145f96c8190a71bb9e442892e68 completed March 7, 2026, 5:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69addf68a8d48190a3360557def67692 completed March 8, 2026, 8:43 p.m.
Created at: March 4, 2026, 7:34 p.m.