Triple

T23051563
Position Surface form Disambiguated ID Type / Status
Subject Eric Guggenheim E574028 entity
Predicate employer P7 FINISHED
Object CBS
CBS is a major American television and radio network known for its wide range of news, entertainment, and sports 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: [Eric Guggenheim, employer, CBS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CBS
Context triple: [Eric Guggenheim, 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 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.
  • C. 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.
  • D. CBS
    CBS is the Curtin Business School, a leading Australian institution offering business education and research as part of Curtin University.
  • E. CBS
    CBS is a premier undergraduate college of the University of Delhi specializing in business, management, and computer science 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: CBS
Triple: [Eric Guggenheim, employer, CBS]
Generated description
CBS is a major American television and radio network known for its wide range of news, entertainment, and sports 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, entertainment, and sports 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_69e245ba7ae48190be606dbc54120e39 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1867d010c8190bc5dba6758d0b797 completed April 29, 2026, 4:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c15a3dfc481909f055d10c263591d completed May 19, 2026, 7:47 a.m.
NEDg Description generation batch_6a0c161cdc3c8190b9695b9c27c743ff completed May 19, 2026, 7:49 a.m.
NED2 Entity disambiguation (via description) batch_6a0c16c73140819088d46d4e8b03c7a4 completed May 19, 2026, 7:52 a.m.
Created at: April 17, 2026, 3:54 p.m.