Triple

T2313496
Position Surface form Disambiguated ID Type / Status
Subject ISO/IEC 9899:1999 E51009 entity
Predicate alsoKnownAs P39 FINISHED
Object C99 E51009 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: C99 | Statement: [ISO/IEC 9899:1999, alsoKnownAs, C99]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: C99
Context triple: [ISO/IEC 9899:1999, alsoKnownAs, C99]
  • A. ISO/IEC 9899 chosen
    ISO/IEC 9899 is the international standard that defines the C programming language’s syntax, semantics, and library.
  • B. C
    C is a foundational, general-purpose programming language known for its efficiency, low-level memory access, and influence on many later languages such as C++, Java, and Python.
  • C. C
    C is a local service on the New York City Subway that runs along the Eighth Avenue Line in Manhattan and continues through Brooklyn.
  • D. CPP
    CPP is a Canadian government-run public pension program that provides retirement, disability, and survivor benefits to eligible contributors.
  • E. CPP
    CPP is a public polytechnic university in Pomona, California, known for its hands-on, learn-by-doing educational approach.
  • 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_69a88b074b908190ae983dbca7757d88 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc61c1ef08190911d5f58c2e91189 completed March 7, 2026, 6:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae895f5420819087b403e9772dce9a completed March 9, 2026, 8:48 a.m.
Created at: March 4, 2026, 7:49 p.m.