Triple

T11958563
Position Surface form Disambiguated ID Type / Status
Subject GNU NYU Ada Translator E284612 entity
Predicate developer P73 FINISHED
Object AdaCore E284613 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: AdaCore | Statement: [GNU NYU Ada Translator, developer, AdaCore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AdaCore
Context triple: [GNU NYU Ada Translator, developer, AdaCore]
  • A. AdaCore chosen
    AdaCore is a software company specializing in high-integrity, safety- and security-critical development tools and compilers for the Ada programming language.
  • B. gnat
    GNAT is a free, open-source Ada compiler and toolchain that is part of the GNU Compiler Collection (GCC).
  • C. Eiffel Software
    Eiffel Software is a software company best known for developing the Eiffel programming language and tools that emphasize object-oriented design and software reliability.
  • D. Embarcadero
    Embarcadero is a historic waterfront district in San Francisco known for its piers, ferry terminal, and scenic promenade along the bay.
  • E. Green Hills Software
    Green Hills Software is an American company specializing in high-reliability, safety- and security-focused embedded software development tools and real-time operating systems.
  • 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.