Triple
T12516943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scheme R5RS |
E299212
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | Scheme language report |
C7088
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: Scheme language report Context triple: [Scheme R5RS, instanceOf, Scheme language report]
-
A.
Lisp dialect
chosen
A Lisp dialect is a specific variant of the Lisp programming language family, defined by its own syntax, semantics, and standard libraries while retaining Lisp’s core features like symbolic expressions and homoiconicity.
-
B.
Lisp machine
A Lisp machine is a specialized computer system designed to efficiently run the Lisp programming language, featuring hardware and software tightly integrated around Lisp’s execution model.
-
C.
programming language implementation
A programming language implementation is the concrete realization of a language’s specification, including its compiler or interpreter, runtime system, and associated tools that translate and execute programs written in that language.
-
D.
programming language design
Programming language design is the process of defining the syntax, semantics, and features of a language to enable humans to express computations clearly, safely, and efficiently for execution by machines.
-
E.
ALGOL family programming language
An ALGOL family programming language is a high-level, block-structured, imperative language descended from the original ALGOL designs, characterized by clear syntax, lexical scoping, and strong influence on later mainstream languages like Pascal, C, and Java.
- F. None of above.
Provenance (1 batch)
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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
Created at: April 8, 2026, 9:57 p.m.