Triple
T2792343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GNU Binutils |
E61957
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | gprof |
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: gprof | Statement: [GNU Binutils, contains, gprof]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: gprof Context triple: [GNU Binutils, contains, gprof]
-
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.
gperftools
gperftools is a Google-developed collection of performance analysis tools for C++ programs, including a fast memory allocator and CPU/heap profilers.
-
C.
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.
-
D.
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.
-
E.
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.
- 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_69ab4b7f51d881908768300ebd2fbdae |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddd107ac81908eb1a6946834eee3 |
completed | March 7, 2026, 8:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc65ebe788190859012e930918b05 |
completed | March 10, 2026, 7:21 a.m. |
Created at: March 6, 2026, 9:58 p.m.