Triple

T23022194
Position Surface form Disambiguated ID Type / Status
Subject R6RS E573197 entity
Predicate languageStandardFor P6195 FINISHED
Object Scheme NE NERFINISHED

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: Scheme | Statement: [R6RS, languageStandardFor, Scheme]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Scheme
Context triple: [R6RS, languageStandardFor, Scheme]
  • A. Scheme chosen
    Scheme is a minimalist, lexically scoped dialect of the Lisp programming language known for its elegant functional programming model and powerful macro system.
  • B. Chez Scheme
    Chez Scheme is a high-performance, optimizing implementation of the Scheme programming language widely used for both research and production systems.
  • C. Racket
    Racket is a modern, multi-paradigm programming language in the Lisp/Scheme family, designed for language-oriented programming, scripting, and education.
  • D. PLT Scheme
    PLT Scheme is the original name of the programming language and environment that later evolved into Racket, known for its powerful support of functional and language-oriented programming.
  • E. MIT Scheme
    MIT Scheme is a long-standing, feature-rich implementation of the Scheme programming language developed at the Massachusetts Institute of Technology, often used for teaching and research in computer science.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245b821008190b0e09cb02092aae1 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f183ea23088190b2f42d9bf01514ac completed April 29, 2026, 4:07 a.m.
Created at: April 17, 2026, 3:52 p.m.