Triple

T563332
Position Surface form Disambiguated ID Type / Status
Subject York University E13500 entity
Predicate affiliation P10 FINISHED
Object COU
COU (Council of Ontario Universities) is a coordinating body that represents and advocates for Ontario’s publicly funded universities.
 E70394 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: COU | Statement: [York University, affiliation, COU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: COU
Context triple: [York University, affiliation, COU]
  • A. COUR
    COUR is the stock ticker symbol for Coursera, a major online learning platform offering courses, certificates, and degrees from universities and companies worldwide.
  • B. CU
    CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
  • C. OC
    OC is the post-nominal designation for Officer of the Order of Canada, one of the country’s highest civilian honors recognizing outstanding achievement and service.
  • D. CUL
    CUL is the main research library of the University of Cambridge and one of the largest and most important academic libraries in the United Kingdom.
  • 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: COU
Triple: [York University, affiliation, COU]
Generated description
COU (Council of Ontario Universities) is a coordinating body that represents and advocates for Ontario’s publicly funded universities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: COU
Target entity description: COU (Council of Ontario Universities) is a coordinating body that represents and advocates for Ontario’s publicly funded universities.
  • A. COUR
    COUR is the stock ticker symbol for Coursera, a major online learning platform offering courses, certificates, and degrees from universities and companies worldwide.
  • B. CU
    CU is the two-letter ISO 3166-1 alpha-2 country code assigned to Cuba.
  • C. OC
    OC is the post-nominal designation for Officer of the Order of Canada, one of the country’s highest civilian honors recognizing outstanding achievement and service.
  • D. CUL
    CUL is the main research library of the University of Cambridge and one of the largest and most important academic libraries in the United Kingdom.
  • 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_69a4933edcf08190b35ecfd6014caee6 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49a712bc48190ba298b3c76ab11cc completed March 1, 2026, 7:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4ed37a98081909afbc0de4079dda8 completed March 2, 2026, 1:51 a.m.
NEDg Description generation batch_69a4ed9314308190ab02cefa0479345d completed March 2, 2026, 1:53 a.m.
NED2 Entity disambiguation (via description) batch_69a4ee076c6481909f18ee53ef936c0f completed March 2, 2026, 1:55 a.m.
Created at: March 1, 2026, 7:32 p.m.