Triple

T11958823
Position Surface form Disambiguated ID Type / Status
Subject lcov E284618 entity
Predicate name P16 FINISHED
Object lcov E284618 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: lcov | Statement: [lcov, name, lcov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: lcov
Context triple: [lcov, name, lcov]
  • A. lcov chosen
    lcov is a graphical front-end and extension for the gcov code coverage tool that collects, processes, and visualizes test coverage data for C and C++ programs.
  • B. 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.
  • 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. SanitizerCoverage
    SanitizerCoverage is an LLVM feature that instruments code to provide fine-grained coverage and runtime checks useful for fuzzing and bug detection.
  • E. Checkmarx
    Checkmarx is a cybersecurity company specializing in application security testing solutions that help organizations identify and remediate vulnerabilities in their software code.
  • 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_69d903681a00819098c2b5260e2ef834 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.