Triple

T17674752
Position Surface form Disambiguated ID Type / Status
Subject Spec# E440617 entity
Predicate uses P98 FINISHED
Object Boogie intermediate verification language — NE NERFINISHED

How this triple was built (3 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: Boogie intermediate verification language | Statement: [Spec#, uses, Boogie intermediate verification language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Boogie intermediate verification language
Context triple: [Spec#, uses, Boogie intermediate verification language]
  • A. Bytecode Alliance
    Bytecode Alliance is a nonprofit industry consortium focused on advancing secure, modular, and portable software through technologies built around WebAssembly.
  • B. Multi-Level Intermediate Representation
    Multi-Level Intermediate Representation is a flexible compiler infrastructure within the LLVM project designed to support multiple abstraction levels and domain-specific optimizations in a unified IR framework.
  • C. SUIF compiler infrastructure
    SUIF compiler infrastructure is a widely used, extensible research framework for building and experimenting with advanced optimizing compilers and program analysis tools.
  • D. Boyer–Moore theorem prover
    The Boyer–Moore theorem prover is an influential automated reasoning system for first-order logic and recursive function theory, notable for pioneering techniques in mechanical proof and program verification.
  • E. SPIR intermediate representation
    SPIR intermediate representation is a standardized, portable intermediate language based on LLVM IR used to enable cross-platform compilation and execution of OpenCL kernels and other heterogeneous compute workloads.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Boogie intermediate verification language
Target entity description: Boogie intermediate verification language is a low-level, language-agnostic formalism designed to serve as a common backend for program verification tools by expressing programs and their correctness properties for automated reasoning.
  • A. Bytecode Alliance
    Bytecode Alliance is a nonprofit industry consortium focused on advancing secure, modular, and portable software through technologies built around WebAssembly.
  • B. Multi-Level Intermediate Representation
    Multi-Level Intermediate Representation is a flexible compiler infrastructure within the LLVM project designed to support multiple abstraction levels and domain-specific optimizations in a unified IR framework.
  • C. SUIF compiler infrastructure
    SUIF compiler infrastructure is a widely used, extensible research framework for building and experimenting with advanced optimizing compilers and program analysis tools.
  • D. Boyer–Moore theorem prover
    The Boyer–Moore theorem prover is an influential automated reasoning system for first-order logic and recursive function theory, notable for pioneering techniques in mechanical proof and program verification.
  • E. SPIR intermediate representation
    SPIR intermediate representation is a standardized, portable intermediate language based on LLVM IR used to enable cross-platform compilation and execution of OpenCL kernels and other heterogeneous compute workloads.
  • F. None of above. chosen

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_69d8b9e87e18819087104a44dc4dc5b1 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e46f6ba22081909e2099490c047378 completed April 19, 2026, 6 a.m.
Created at: April 10, 2026, 10 a.m.