Triple

T5923206
Position Surface form Disambiguated ID Type / Status
Subject Racket E131743 entity
Predicate implementationLanguage P18654 FINISHED
Object Racket E131743 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: Racket | Statement: [Racket, implementationLanguage, Racket]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Racket
Context triple: [Racket, implementationLanguage, Racket]
  • A. Racket chosen
    Racket is a modern, multi-paradigm programming language in the Lisp/Scheme family, designed for language-oriented programming, scripting, and education.
  • 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. Scheme
    Scheme is a minimalist, lexically scoped dialect of the Lisp programming language known for its elegant functional programming model and powerful macro system.
  • D. Gambit Scheme
    Gambit Scheme is a high-performance implementation of the Scheme programming language, known for its efficient compiler, support for concurrent and distributed programming, and ability to generate C code for portability.
  • 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 (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_69c0085a1ed08190a7e9a8b6323fd680 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03804d9808190829a418adb7864aa completed March 22, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c0483e3481908e50f8b34b11a878 completed March 23, 2026, 4:23 a.m.
Created at: March 22, 2026, 4 p.m.