Triple

T11959091
Position Surface form Disambiguated ID Type / Status
Subject Clang-Tidy E284623 entity
Predicate usesInfrastructure P6820 FINISHED
Object LLVM libraries 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 libraries | Statement: [Clang-Tidy, usesInfrastructure, LLVM libraries]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LLVM libraries
Context triple: [Clang-Tidy, usesInfrastructure, LLVM libraries]
  • 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. libclang library
    The libclang library is a C interface to the Clang compiler’s parsing and analysis capabilities, enabling tools to programmatically inspect, analyze, and manipulate C-family source code.
  • C. LLDB
    LLDB is a modern, high-performance debugger primarily used with the LLVM toolchain for languages like C, C++, and Objective-C.
  • D. 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.
  • E. 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.
  • 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_69d6ab2db38c8190b1f0ed6663ef8ada completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9036941948190b150369094551731 completed April 10, 2026, 2:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69f459210d1c8190953cd01da3d2ad04 completed May 1, 2026, 7:41 a.m.
Created at: April 8, 2026, 9:45 p.m.