Triple

T12281585
Position Surface form Disambiguated ID Type / Status
Subject D (via LDC) E292727 entity
Predicate supportsFeature P203 FINISHED
Object LLVM optimization passes 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 optimization passes | Statement: [D (via LDC), supportsFeature, LLVM optimization passes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LLVM optimization passes
Context triple: [D (via LDC), supportsFeature, LLVM optimization passes]
  • 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. GCC back end
    The GCC back end is the code-generation component of the GNU Compiler Collection that translates language-specific intermediate representations into optimized machine code for various hardware architectures.
  • 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. CIRCT
    CIRCT is an open-source LLVM subproject that provides a set of reusable compiler infrastructure and tools for hardware design and synthesis using MLIR.
  • E. Partial Evaluation and Program Manipulation
    Partial Evaluation and Program Manipulation (PEPM) is a specialized conference and research area in computer science focused on techniques for program transformation, optimization, and analysis through partial evaluation and related methods.
  • 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_69d6ab690ad081908c0ed3870ec82d53 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cf2b09c81908a11581d33f65be0 completed April 10, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e70dec8819098199fbb54d888c1 completed May 2, 2026, 3:55 p.m.
Created at: April 8, 2026, 9:52 p.m.