Triple

T2629598
Position Surface form Disambiguated ID Type / Status
Subject gprof E59600 entity
Predicate documentation P4310 FINISHED
Object GNU gprof manual E59600 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: GNU gprof manual | Statement: [gprof, documentation, GNU gprof manual]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GNU gprof manual
Context triple: [gprof, documentation, GNU gprof manual]
  • A. gprof chosen
    gprof is a performance analysis tool that profiles program execution to help developers identify time-consuming functions and optimize their code.
  • B. perf (Linux profiler)
    perf (Linux profiler) is a powerful Linux profiling and performance analysis tool that leverages kernel performance counters to measure and diagnose system and application behavior.
  • C. gperftools
    gperftools is a Google-developed collection of performance analysis tools for C++ programs, including a fast memory allocator and CPU/heap profilers.
  • D. Valgrind callgrind
    Valgrind callgrind is a profiling tool within the Valgrind framework that analyzes program performance by collecting detailed information about function calls and instruction-level execution costs.
  • E. gcov
    gcov is a test coverage analysis tool used with GCC to measure and report how much of a program’s source code is executed during runtime.
  • 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_69ab4ac8596c8190b34997e73d9e991c completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd8c452508190b02e1630d725497a completed March 7, 2026, 7:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98b93a108190b21f4af3e8c16c2b completed March 10, 2026, 4:06 a.m.
Created at: March 6, 2026, 9:50 p.m.