Triple

T8188902
Position Surface form Disambiguated ID Type / Status
Subject Canadian Special Operations Regiment E191254 entity
Predicate nickname P55 FINISHED
Object CSOR E718140 NE FINISHED

How this triple was built (2 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: CSOR | Statement: [Canadian Special Operations Regiment, nickname, CSOR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CSOR
Context triple: [Canadian Special Operations Regiment, nickname, CSOR]
  • A. CSOR chosen
    CSOR is an elite Canadian special operations unit specializing in high-risk missions such as counterterrorism, direct action, and special reconnaissance in support of national and international security objectives.
  • B. CSE
    CSE is the abbreviated name for the University of Edinburgh’s College of Science and Engineering, a major academic division focused on scientific and engineering disciplines.
  • C. CSE
    CSE is Canada’s national cryptologic agency responsible for foreign signals intelligence, cybersecurity, and protecting government communications and information systems.
  • D. CSE
    CSE is the College of Science and Engineering at the University of Minnesota, a major academic unit focused on engineering, physical sciences, and related disciplines.
  • E. CSE
    CSE is a highly competitive nationwide examination in India conducted by the Union Public Service Commission to recruit candidates into the country’s civil services, including the IAS, IPS, and IFS.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca82c5b6948190a583c096fb0a6c71 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4da0e1288190b9c7c1d3b9a98830 completed March 31, 2026, 4:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd3495a2808190844cbd8e22458ebc completed April 1, 2026, 3:07 p.m.
Created at: March 30, 2026, 5:41 p.m.