Triple

T13635180
Position Surface form Disambiguated ID Type / Status
Subject Justin Hartley E325829 entity
Predicate employer P7 FINISHED
Object CBS
CBS is a major American broadcast television network known for its wide range of popular dramas, comedies, and news 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: [Justin Hartley, employer, CBS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CBS
Context triple: [Justin Hartley, employer, CBS]
  • A. CBS
    CBS is a leading Danish university in Copenhagen specializing in business and economics education and research.
  • 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 a college within the University of California, Davis that focuses on education and research in the biological sciences.
  • D. CBS
    CBS is a Harvard University research center dedicated to advancing the understanding of the brain through interdisciplinary neuroscience studies.
  • E. 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.
  • 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: [Justin Hartley, employer, CBS]
Generated description
CBS is a major American broadcast television network known for its wide range of popular dramas, comedies, and news programming.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CBS
Target entity description: CBS is a major American broadcast television network known for its wide range of popular dramas, comedies, and news 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_69d8076beddc8190a53156f5bea77f5e completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc5a616dc81908b8c1213e1d4beed completed April 12, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69f794307c288190a0f4629bf5e2b0d9 completed May 3, 2026, 6:30 p.m.
NEDg Description generation batch_69f79655d5f08190a3cbf3e12e2ffa67 completed May 3, 2026, 6:39 p.m.
NED2 Entity disambiguation (via description) batch_69f7972a1cf48190a1d435227414967a completed May 3, 2026, 6:42 p.m.
Created at: April 9, 2026, 9:51 p.m.