Triple
T23022232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R6RS |
E573197
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | R6RS non-normative appendices |
—
|
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: R6RS non-normative appendices | Statement: [R6RS, hasComponent, R6RS non-normative appendices]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: R6RS non-normative appendices Context triple: [R6RS, hasComponent, R6RS non-normative appendices]
-
A.
R6RS
chosen
R6RS is the sixth revision of the Scheme programming language standard, defining its core language features, libraries, and semantics.
-
B.
R3RS
R3RS is the third revision of the Revised^n Report on the Algorithmic Language Scheme, specifying a standardized version of the Scheme programming language.
-
C.
R4RS
R4RS is the fourth revised report on the Scheme programming language standard, defining its core syntax, semantics, and standard procedures.
-
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.
RnRS
RnRS is the standard specification document series that formally defines the Scheme programming language.
- 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.