Triple
T12280927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | compiler-rt |
E292713
|
entity |
| Predicate | supports |
P516
|
FINISHED |
| Object | SanitizerCoverage |
E292719
|
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: SanitizerCoverage | Statement: [compiler-rt, supports, SanitizerCoverage]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SanitizerCoverage Context triple: [compiler-rt, supports, SanitizerCoverage]
-
A.
SanitizerCoverage
chosen
SanitizerCoverage is an LLVM feature that instruments code to provide fine-grained coverage and runtime checks useful for fuzzing and bug detection.
-
B.
PureCoverage
PureCoverage is a software testing tool from Pure Software designed to measure and analyze code coverage to improve software quality and reliability.
-
C.
dotCover
dotCover is a .NET unit test runner and code coverage tool designed to help developers measure and improve test coverage in Visual Studio.
-
D.
AddressSanitizer
AddressSanitizer is a fast memory error detector that instruments programs to find issues like buffer overflows and use-after-free bugs at runtime.
-
E.
GNATcoverage
GNATcoverage is an AdaCore tool that measures and reports structural code coverage for Ada and other languages, supporting rigorous verification and certification needs.
- 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.