Triple
T1160245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scheme |
E24474
|
entity |
| Predicate | notableImplementation |
P102
|
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: [Scheme, notableImplementation, Racket]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Racket Context triple: [Scheme, notableImplementation, 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.
Scheme
Scheme is a minimalist, lexically scoped dialect of the Lisp programming language known for its elegant functional programming model and powerful macro system.
-
C.
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.
-
D.
GNU Guile
GNU Guile is the official extension language platform of the GNU Project, providing a Scheme-based scripting and programming environment for extending and customizing applications.
-
E.
Lisp programming language
Lisp is a pioneering high-level programming language, especially influential in artificial intelligence research and known for its symbolic processing and distinctive parenthesized syntax.
- 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_69a494060e148190abb42f971242c197 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bcaf3a9081908bad2eba74dffbc1 |
completed | March 1, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac667d2bdc8190b7d797683a4d3fe8 |
completed | March 7, 2026, 5:55 p.m. |
Created at: March 1, 2026, 7:45 p.m.