Triple

T7935453
Position Surface form Disambiguated ID Type / Status
Subject Council of Canadian Academies E184277 entity
Predicate shortName P43 FINISHED
Object CCA
CCA is an independent, not-for-profit organization in Canada that conducts expert assessments to inform public policy and decision-making on scientific and scholarly issues.
 E700415 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: CCA | Statement: [Council of Canadian Academies, shortName, CCA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CCA
Context triple: [Council of Canadian Academies, shortName, CCA]
  • A. CCA
    CCA is the ICAO airline designator used to identify Air China in international aviation operations.
  • B. CCA
    CCA is the highest state court in Texas for criminal cases, serving as the court of last resort for all criminal matters in the state.
  • C. CCA
    CCA is the commonly used abbreviation for the Canada Council for the Arts, Canada’s national public arts funding and advocacy agency.
  • D. CAC
    The Central American Cup (CAC) is a regional football tournament featuring national teams from Central America competing for the championship title.
  • E. CAC
    CAC is the Computing Accreditation Commission, a specialized body that accredits computing-related degree programs to ensure they meet established quality and professional standards.
  • 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: CCA
Triple: [Council of Canadian Academies, shortName, CCA]
Generated description
CCA is an independent, not-for-profit organization in Canada that conducts expert assessments to inform public policy and decision-making on scientific and scholarly issues.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CCA
Target entity description: CCA is an independent, not-for-profit organization in Canada that conducts expert assessments to inform public policy and decision-making on scientific and scholarly issues.
  • A. CCA
    CCA is the ICAO airline designator used to identify Air China in international aviation operations.
  • B. CCA
    CCA is the highest state court in Texas for criminal cases, serving as the court of last resort for all criminal matters in the state.
  • C. CCA
    CCA is the commonly used abbreviation for the Canada Council for the Arts, Canada’s national public arts funding and advocacy agency.
  • D. CAC
    The Central American Cup (CAC) is a regional football tournament featuring national teams from Central America competing for the championship title.
  • E. CAC
    CAC is the abbreviated designation for the Chief of the Air Corps, the head of the former United States Army Air Corps prior to the establishment of the U.S. Air Force.
  • 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3aec394081909a9569c02ac372af completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5c0791e48190af18299c22f6a804 completed March 31, 2026, 5:30 a.m.
NEDg Description generation batch_69cb7633c5a0819089deb6e89d9acb8e completed March 31, 2026, 7:22 a.m.
NED2 Entity disambiguation (via description) batch_69cbb84dc86c8190893d67ce07c51aa0 completed March 31, 2026, 12:04 p.m.
Created at: March 30, 2026, 5:08 p.m.