Triple

T2716454
Position Surface form Disambiguated ID Type / Status
Subject LLVM E59978 entity
Predicate hasComponent P35 FINISHED
Object OpenMP runtime E59596 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: OpenMP runtime | Statement: [LLVM, hasComponent, OpenMP runtime]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OpenMP runtime
Context triple: [LLVM, hasComponent, OpenMP runtime]
  • A. OpenMP chosen
    OpenMP is an application programming interface that supports multi-platform shared-memory parallel programming in C, C++, and Fortran.
  • B. OMPS
    OMPS (Ozone Mapping and Profiler Suite) is a satellite-based instrument system designed to measure global ozone distribution and monitor atmospheric ozone layer changes from orbit.
  • C. Mono runtime
    Mono runtime is an open-source implementation of Microsoft’s .NET framework that enables cross-platform execution of .NET applications on systems such as Linux, macOS, and mobile devices.
  • D. OpenACC
    OpenACC is a directive-based parallel programming standard designed to simplify the development of portable, high-performance code on heterogeneous systems such as GPUs and multicore CPUs.
  • E. OpenCL
    OpenCL is an open, cross-platform framework for writing programs that execute across heterogeneous systems including CPUs, GPUs, and other processors.
  • 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_69ab4ac92a088190bc74bca14038e3de completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abda964d4881908179b2a1b16411e4 completed March 7, 2026, 7:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69afb68c3ccc81909995d17651af27ed completed March 10, 2026, 6:13 a.m.
Created at: March 6, 2026, 9:55 p.m.