Triple

T5794588
Position Surface form Disambiguated ID Type / Status
Subject Central University of Technology E128476 entity
Predicate abbreviation P43 FINISHED
Object CUT
CUT is the commonly used acronym for the Central University of Technology, a higher education institution in South Africa.
 E546546 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: CUT | Statement: [Central University of Technology, abbreviation, CUT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CUT
Context triple: [Central University of Technology, abbreviation, CUT]
  • A. CUT
    CUT is a public university in Limassol, Cyprus, known for its focus on applied research and technology-oriented academic programs.
  • B. CUT
    CUT is the National Rail station code assigned to Cutty Sark DLR station in London.
  • C. Cuts
    Cuts is an American television sitcom that aired on UPN, featuring Shannon Elizabeth in a comedic role set around a family-owned barbershop.
  • D. The Cut
    The Cut is a digital publication and vertical of New York Magazine that focuses on fashion, culture, politics, and women’s issues.
  • E. In the Cut
    In the Cut is a 2003 neo-noir erotic thriller film directed by Jane Campion, known for its gritty exploration of female sexuality and urban violence in contemporary New York City.
  • 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: CUT
Triple: [Central University of Technology, abbreviation, CUT]
Generated description
CUT is the commonly used acronym for the Central University of Technology, a higher education institution in South Africa.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CUT
Target entity description: CUT is the commonly used acronym for the Central University of Technology, a higher education institution in South Africa.
  • A. CUT
    CUT is a public university in Limassol, Cyprus, known for its focus on applied research and technology-oriented academic programs.
  • B. CUT
    CUT is the National Rail station code assigned to Cutty Sark DLR station in London.
  • C. Cuts
    Cuts is an American television sitcom that aired on UPN, featuring Shannon Elizabeth in a comedic role set around a family-owned barbershop.
  • D. The Cut
    The Cut is a digital publication and vertical of New York Magazine that focuses on fashion, culture, politics, and women’s issues.
  • E. In the Cut
    In the Cut is a 2003 neo-noir erotic thriller film directed by Jane Campion, known for its gritty exploration of female sexuality and urban violence in contemporary New York City.
  • 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_69c00845ca68819081a2ce3ecca577f7 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02a91c7788190936671bf816d3772 completed March 22, 2026, 5:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c098286c1c8190b77cbaeda327dba4 completed March 23, 2026, 1:32 a.m.
NEDg Description generation batch_69c098a0325c81909a1326b94e40ed50 completed March 23, 2026, 1:34 a.m.
NED2 Entity disambiguation (via description) batch_69c09943deec819085992c4e44050a34 completed March 23, 2026, 1:37 a.m.
Created at: March 22, 2026, 3:51 p.m.