Triple

T272210
Position Surface form Disambiguated ID Type / Status
Subject Canada CIFAR AI Chair E5657 entity
Predicate administeredBy P86 FINISHED
Object CIFAR
CIFAR (the Canadian Institute for Advanced Research) is a Canadian global research organization that supports long-term, collaborative, interdisciplinary research, including major initiatives in artificial intelligence.
E35343 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: CIFAR | Statement: [Canada CIFAR AI Chair, administeredBy, CIFAR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CIFAR
Context triple: [Canada CIFAR AI Chair, administeredBy, CIFAR]
  • A. LeNet
    LeNet is one of the earliest convolutional neural network architectures, pioneering modern deep learning approaches to image recognition and handwritten digit classification.
  • B. CAF
    CAF is the Confederation of African Football, the governing body for association football in Africa and one of FIFA’s six continental confederations.
  • C. RBM
    RBM is a global partnership initiative dedicated to coordinating and scaling up efforts to prevent, control, and ultimately eliminate malaria worldwide.
  • D. DALL·E
    DALL·E is an AI model developed by OpenAI that generates images from natural language descriptions, enabling text-to-image synthesis.
  • E. CIT
    CIT is the commonly used acronym for the Center for Information Technology, an organization focused on advancing computing and information systems.
  • 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: CIFAR
Triple: [Canada CIFAR AI Chair, administeredBy, CIFAR]
Generated description
CIFAR (the Canadian Institute for Advanced Research) is a Canadian global research organization that supports long-term, collaborative, interdisciplinary research, including major initiatives in artificial intelligence.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: CIFAR
Target entity description: CIFAR (the Canadian Institute for Advanced Research) is a Canadian global research organization that supports long-term, collaborative, interdisciplinary research, including major initiatives in artificial intelligence.
  • A. LeNet
    LeNet is one of the earliest convolutional neural network architectures, pioneering modern deep learning approaches to image recognition and handwritten digit classification.
  • B. CAF
    CAF is the Confederation of African Football, the governing body for association football in Africa and one of FIFA’s six continental confederations.
  • C. RBM
    RBM is a global partnership initiative dedicated to coordinating and scaling up efforts to prevent, control, and ultimately eliminate malaria worldwide.
  • D. DALL·E
    DALL·E is an AI model developed by OpenAI that generates images from natural language descriptions, enabling text-to-image synthesis.
  • E. CIT
    CIT is the commonly used acronym for the Center for Information Technology, an organization focused on advancing computing and information systems.
  • 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_69a25853594c8190b05ec3a586ec88bf completed Feb. 28, 2026, 2:52 a.m.
NER Named-entity recognition batch_69a25dcf667c8190a7b8630fe67b9a90 completed Feb. 28, 2026, 3:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69a38f537f1c8190a59ac4669498a3fc completed March 1, 2026, 12:58 a.m.
NEDg Description generation batch_69a38fbfac808190b2b551dcbfe6faff completed March 1, 2026, 1 a.m.
NED2 Entity disambiguation (via description) batch_69a3903779e88190a00c44a522e82022 completed March 1, 2026, 1:02 a.m.
Created at: Feb. 28, 2026, 2:57 a.m.