Triple

T20718480
Position Surface form Disambiguated ID Type / Status
Subject Nancy Travis E509241 entity
Predicate employer P7 FINISHED
Object CBS
CBS is a major American television network known for broadcasting a wide range of popular 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: [Nancy Travis, employer, CBS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CBS
Context triple: [Nancy Travis, 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: [Nancy Travis, employer, CBS]
Generated description
CBS is a major American television network known for broadcasting a wide range of popular 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 network known for broadcasting a wide range of popular 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 college within the University of California, Davis that focuses on education and research in the biological sciences.
  • 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_69e0b4c4cc648190b45fda6e2b20af56 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c1d39bec8190b3642b0d6d833375 completed April 21, 2026, 12:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a08e04f58648190acf2cdc03ada05a4 completed May 16, 2026, 9:23 p.m.
NEDg Description generation batch_6a08e15d93ec8190bbe859fb42a4a5ac completed May 16, 2026, 9:27 p.m.
NED2 Entity disambiguation (via description) batch_6a08e25d8cb08190ba75b792aac192ab completed May 16, 2026, 9:32 p.m.
Created at: April 16, 2026, 12:25 p.m.