Triple

T23259101
Position Surface form Disambiguated ID Type / Status
Subject WASI component model E581954 entity
Predicate designedBy P184 FINISHED
Object Bytecode Alliance 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: Bytecode Alliance | Statement: [WASI component model, designedBy, Bytecode Alliance]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bytecode Alliance
Context triple: [WASI component model, designedBy, Bytecode Alliance]
  • A. Bytecode Alliance chosen
    Bytecode Alliance is a nonprofit industry consortium focused on advancing secure, modular, and portable software through technologies built around WebAssembly.
  • B. RISC-V International
    RISC-V International is the global nonprofit consortium that oversees the development, standardization, and promotion of the open RISC-V instruction set architecture.
  • C. Zig Software Foundation
    The Zig Software Foundation is the organization responsible for stewarding the development, ecosystem, and community of the Zig programming language.
  • D. LLVM
    LLVM is a modular, reusable compiler and toolchain infrastructure project widely used for building language frontends, optimizers, and backends for diverse hardware architectures.
  • E. RISC-V
    RISC-V is an open, extensible instruction set architecture (ISA) based on the reduced instruction set computing (RISC) principles, widely used for research, embedded systems, and increasingly general-purpose computing.
  • 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_69e246079f58819085eaa9c260906880 completed April 17, 2026, 2:39 p.m.
NER Named-entity recognition batch_69f194c710c48190aff03d210642a043 completed April 29, 2026, 5:19 a.m.
Created at: April 17, 2026, 4:11 p.m.