Triple

T94538
Position Surface form Disambiguated ID Type / Status
Subject Guido van Rossum E1899 entity
Predicate programmingLanguage P1592 FINISHED
Object 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.
E9269 NE FINISHED

How this triple was built (4 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: [Guido van Rossum, programmingLanguage, C]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: C
Context triple: [Guido van Rossum, programmingLanguage, C]
  • A. .cl
    .cl is the country code top-level domain (ccTLD) assigned to Chile for use on the internet.
  • B. CCC
    The CCC, or Civilian Conservation Corps, was a New Deal work relief program in the United States during the 1930s and early 1940s that employed young men in conservation and public works projects such as reforestation, park development, and soil erosion control.
  • C. CUL
    CUL is the main research library of the University of Cambridge and one of the largest and most important academic libraries in the United Kingdom.
  • D. COT
    COT is the standard time observed in Colombia, corresponding to UTC−05:00 without daylight saving time.
  • E. SCC
    SCC is the commonly used abbreviation for the MIT Schwarzman College of Computing, an interdisciplinary hub for computing and AI research and education.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: C
Triple: [Guido van Rossum, programmingLanguage, C]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: C
Target entity description: 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.
  • A. .cl
    .cl is the country code top-level domain (ccTLD) assigned to Chile for use on the internet.
  • B. CCC
    The CCC, or Civilian Conservation Corps, was a New Deal work relief program in the United States during the 1930s and early 1940s that employed young men in conservation and public works projects such as reforestation, park development, and soil erosion control.
  • C. CUL
    CUL is the main research library of the University of Cambridge and one of the largest and most important academic libraries in the United Kingdom.
  • D. COT
    COT is the standard time observed in Colombia, corresponding to UTC−05:00 without daylight saving time.
  • E. SCC
    SCC is the commonly used abbreviation for the MIT Schwarzman College of Computing, an interdisciplinary hub for computing and AI research and education.
  • F. None of above. chosen

Provenance (5 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_69a24d4862f881908cc8b89d3a78031d completed Feb. 28, 2026, 2:04 a.m.
NER Named-entity recognition batch_69a24fd4777c81909ea9b9a6bd4f7ad5 completed Feb. 28, 2026, 2:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69a266ebb994819085fb84dd1d2d25ad completed Feb. 28, 2026, 3:54 a.m.
NEDg Description generation batch_69a267b826a48190aafc1219e8966ffe completed Feb. 28, 2026, 3:57 a.m.
NED2 Entity disambiguation (via description) batch_69a268227ecc8190bb4b4149a7e15923 completed Feb. 28, 2026, 3:59 a.m.
Created at: Feb. 28, 2026, 2:09 a.m.