Triple

T1935010
Position Surface form Disambiguated ID Type / Status
Subject XNU E41424 entity
Predicate programmingLanguage P1592 FINISHED
Object C E9269 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: C | Statement: [XNU, programmingLanguage, C]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: C
Context triple: [XNU, programmingLanguage, C]
  • A. 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.
  • B. C chosen
    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. CPP
    CPP is a Canadian government-run public pension program that provides retirement, disability, and survivor benefits to eligible contributors.
  • D. CPP
    CPP is a public polytechnic university in Pomona, California, known for its hands-on, learn-by-doing educational approach.
  • E. .cc
    .cc is the country code top-level domain (ccTLD) assigned to the Cocos (Keeling) Islands, often marketed globally for a variety of commercial and creative uses.
  • 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_69a88649b24c819080047f26b6db2ded completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb29c7be08190986df157bf5d7c9e completed March 7, 2026, 5:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3f3932081909a72d1022259359e completed March 8, 2026, 10:10 p.m.
Created at: March 4, 2026, 7:35 p.m.