Triple
T12516945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scheme R5RS |
E299212
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | R5RS |
E299212
|
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: R5RS | Statement: [Scheme R5RS, shortName, R5RS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: R5RS Context triple: [Scheme R5RS, shortName, R5RS]
-
A.
R6RS
R6RS is the sixth revision of the Scheme programming language standard, defining its core language features, libraries, and semantics.
-
B.
R4RS
R4RS is the fourth revised report on the Scheme programming language standard, defining its core syntax, semantics, and standard procedures.
-
C.
Scheme R5RS
chosen
Scheme R5RS is the fifth revised report of the Scheme programming language standard, defining its core syntax, semantics, and standard libraries.
-
D.
R7RS (small) (partial)
R7RS (small) (partial) is a subset of the Revised⁷ Report on the Algorithmic Language Scheme standard that defines a core, lightweight version of the Scheme programming language.
-
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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9541f80148190976d1d912fe155d0 |
completed | April 10, 2026, 7:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64bbd58b88190baeb99380babf64f |
completed | May 2, 2026, 7:08 p.m. |
Created at: April 8, 2026, 9:57 p.m.