Triple

T1241147
Position Surface form Disambiguated ID Type / Status
Subject Cyprus University of Technology E26659 entity
Predicate abbreviation P43 FINISHED
Object CUT
CUT is a public university in Limassol, Cyprus, known for its focus on applied research and technology-oriented academic programs.
 E142310 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: [Cyprus University of Technology, abbreviation, CUT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CUT
Context triple: [Cyprus University of Technology, abbreviation, CUT]
  • A. Cuts
    Cuts is an American television sitcom that aired on UPN, featuring Shannon Elizabeth in a comedic role set around a family-owned barbershop.
  • B. Cuts (TV series)
    Cuts is an American sitcom that aired on UPN in the mid-2000s, focusing on the comedic ups and downs of running a family-owned barbershop in Baltimore.
  • C. Deep Cut
    Deep Cut is a historic Civil War battlefield site within Manassas National Battlefield Park, notable for intense fighting during the Second Battle of Bull Run.
  • D. Short Cuts
    Short Cuts is a Toronto International Film Festival program showcasing a curated selection of international and Canadian short films across genres and styles.
  • E. COT
    COT is the standard time observed in Colombia, corresponding to UTC−05:00 without daylight saving time.
  • 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: [Cyprus University of Technology, abbreviation, CUT]
Generated description
CUT is a public university in Limassol, Cyprus, known for its focus on applied research and technology-oriented academic programs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CUT
Target entity description: CUT is a public university in Limassol, Cyprus, known for its focus on applied research and technology-oriented academic programs.
  • A. Cuts
    Cuts is an American television sitcom that aired on UPN, featuring Shannon Elizabeth in a comedic role set around a family-owned barbershop.
  • B. Cuts (TV series)
    Cuts is an American sitcom that aired on UPN in the mid-2000s, focusing on the comedic ups and downs of running a family-owned barbershop in Baltimore.
  • C. Deep Cut
    Deep Cut is a historic Civil War battlefield site within Manassas National Battlefield Park, notable for intense fighting during the Second Battle of Bull Run.
  • D. Short Cuts
    Short Cuts is a Toronto International Film Festival program showcasing a curated selection of international and Canadian short films across genres and styles.
  • E. COT
    COT is the standard time observed in Colombia, corresponding to UTC−05:00 without daylight saving time.
  • 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_69a4948689d08190b3a4a3f388c02148 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4bf4343e48190a232abd8475880a0 completed March 1, 2026, 10:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac8f79afe08190802dd615f01e303d completed March 7, 2026, 8:50 p.m.
NEDg Description generation batch_69ac90277d2481908d358bf3f8fdbdca completed March 7, 2026, 8:52 p.m.
NED2 Entity disambiguation (via description) batch_69ac9080f4748190a2313bede48d3404 completed March 7, 2026, 8:54 p.m.
Created at: March 1, 2026, 7:47 p.m.