Triple

T17600903
Position Surface form Disambiguated ID Type / Status
Subject Christian LeBlanc E428696 entity
Predicate employer P7 FINISHED
Object CBS
CBS is a major American television and radio network known for its wide range of news, sports, and entertainment programming.
E6070 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: CBS | Statement: [Christian LeBlanc, employer, CBS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CBS
Context triple: [Christian LeBlanc, employer, CBS]
  • A. CBS
    CBS is a leading Danish university in Copenhagen specializing in business and economics education and research.
  • B. CBS
    CBS is the National Rail station code assigned to Coatbridge Sunnyside railway station in North Lanarkshire, Scotland.
  • C. CBS
    CBS is the commonly used abbreviation for the Commission for Basic Systems, a specialized body focused on foundational infrastructure and standards, likely within an international or governmental organizational context.
  • D. CBS
    CBS is the acronym for the Central Bank of Somalia, the country’s primary monetary authority responsible for issuing currency and overseeing financial stability.
  • E. CBS
    CBS is the Curtin Business School, a leading Australian institution offering business education and research as part of Curtin University.
  • 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: CBS
Triple: [Christian LeBlanc, employer, CBS]
Generated description
CBS is a major American television and radio network known for its wide range of news, sports, and entertainment programming.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: CBS
Target entity description: CBS is a major American television and radio network known for its wide range of news, sports, and entertainment programming.
  • A. CBS chosen
    CBS is a major American broadcast television network known for airing a wide range of popular news, sports, and entertainment programming nationwide.
  • B. CBS
    CBS is a leading graduate business school of Columbia University in New York City, renowned for its MBA and finance programs.
  • C. CBS
    CBS is the national statistical office of the Netherlands responsible for collecting, analyzing, and publishing data on the country’s economy, population, and society.
  • D. CBS
    CBS is the commonly used abbreviation for the Commission for Basic Systems, a specialized body focused on foundational infrastructure and standards, likely within an international or governmental organizational context.
  • E. CBS
    CBS is a Harvard University research center dedicated to advancing the understanding of the brain through interdisciplinary neuroscience studies.
  • F. None of above.

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_69d889e1c6148190ba76241e74688f8b completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46c48dfc08190ba360e6082cffa87 completed April 19, 2026, 5:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01e81b951c81908969e6d2f952efc4 completed May 11, 2026, 2:30 p.m.
NEDg Description generation batch_6a01ef0a9fb48190ac9d38f027ceb728 completed May 11, 2026, 3 p.m.
NED2 Entity disambiguation (via description) batch_6a01ef87c62c8190b9a3cd936542d7b4 completed May 11, 2026, 3:02 p.m.
Created at: April 10, 2026, 5:51 a.m.