Triple
T12020732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | C++23 (partial) |
E286140
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | C++17 |
E13747
|
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: C++17 | Statement: [C++23 (partial), relatedTo, C++17]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: C++17 Context triple: [C++23 (partial), relatedTo, C++17]
-
A.
C++23 (partial)
C++23 (partial) refers to the subset of features from the C++23 language standard that have been implemented and are usable in a given compiler, such as Clang, before full standard support is complete.
-
B.
C++
chosen
C++ is a high-performance, general-purpose programming language widely used for system/software development, game engines, and performance-critical applications.
-
C.
C++ standard library
The C++ standard library is a collection of ready-made classes and functions that provide core utilities such as containers, algorithms, input/output, and threading support for C++ programs.
-
D.
CPP
CPP is a Canadian government-run public pension program that provides retirement, disability, and survivor benefits to eligible contributors.
-
E.
CPP
CPP is a public polytechnic university in Pomona, California, known for its hands-on, learn-by-doing educational approach.
- 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_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903ed15408190afc21afd57d6a737 |
completed | April 10, 2026, 2:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f48b62cad8819092beb72c604a4762 |
completed | May 1, 2026, 11:15 a.m. |
Created at: April 8, 2026, 9:47 p.m.