Triple
T4391081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PlaidML |
E99362
|
entity |
| Predicate | supportsBackend |
P15794
|
FINISHED |
| Object | LLVM |
E59978
|
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: LLVM | Statement: [PlaidML, supportsBackend, LLVM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LLVM Context triple: [PlaidML, supportsBackend, LLVM]
-
A.
LLVM
chosen
LLVM is a modular, reusable compiler and toolchain infrastructure project widely used for building language frontends, optimizers, and backends for diverse hardware architectures.
-
B.
Clang
Clang is a modern, open-source C, C++, and Objective-C compiler front end for the LLVM project, known for its fast compilation, expressive diagnostics, and modular design.
-
C.
MLIR
MLIR (Multi-Level Intermediate Representation) is a flexible compiler infrastructure and intermediate representation framework designed to support reusable, extensible optimizations and code generation across diverse domains and hardware targets.
-
D.
Bytecode Alliance
Bytecode Alliance is a nonprofit industry consortium focused on advancing secure, modular, and portable software through technologies built around WebAssembly.
-
E.
LLDB
LLDB is a modern, high-performance debugger primarily used with the LLVM toolchain for languages like C, C++, and Objective-C.
- 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_69b3454f739481909ff6c28331f0c0b9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b352843d7c8190929b94c94eaa63df |
completed | March 12, 2026, 11:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5e530428881908d125971263bd747 |
completed | March 14, 2026, 10:46 p.m. |
Created at: March 12, 2026, 11:19 p.m.