Triple

T2992784
Position Surface form Disambiguated ID Type / Status
Subject Royal Military College of Canada E80994 entity
Predicate abbreviation P43 FINISHED
Object RMCC
RMCC is a Canadian military academy and degree-granting university that educates and trains officer cadets for service in the Canadian Armed Forces.
 E317454 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: RMCC | Statement: [Royal Military College of Canada, abbreviation, RMCC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: RMCC
Context triple: [Royal Military College of Canada, abbreviation, RMCC]
  • A. MCC
    MCC is the abbreviated name of Belgium’s naval branch within the Belgian Armed Forces.
  • B. MCC
    MCC is a U.S. foreign aid agency that provides time-limited grants to promote economic growth, reduce poverty, and strengthen institutions in developing countries.
  • C. RMC
    RMC is the Royal Military College at Duntroon, Australia’s principal officer training academy for the Australian Army.
  • D. RKC
    RKC is the commonly used abbreviation for the Revised Kyoto Convention, an international agreement that standardizes and simplifies customs procedures worldwide.
  • E. KMC
    KMC is the municipal governing body responsible for providing and managing civic services and infrastructure in Karachi, Pakistan.
  • 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: RMCC
Triple: [Royal Military College of Canada, abbreviation, RMCC]
Generated description
RMCC is a Canadian military academy and degree-granting university that educates and trains officer cadets for service in the Canadian Armed Forces.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: RMCC
Target entity description: RMCC is a Canadian military academy and degree-granting university that educates and trains officer cadets for service in the Canadian Armed Forces.
  • A. MCC
    MCC is the abbreviated name of Belgium’s naval branch within the Belgian Armed Forces.
  • B. MCC
    MCC is a U.S. foreign aid agency that provides time-limited grants to promote economic growth, reduce poverty, and strengthen institutions in developing countries.
  • C. RMC
    RMC is the Royal Military College at Duntroon, Australia’s principal officer training academy for the Australian Army.
  • D. RKC
    RKC is the commonly used abbreviation for the Revised Kyoto Convention, an international agreement that standardizes and simplifies customs procedures worldwide.
  • E. KMC
    KMC is the municipal governing body responsible for providing and managing civic services and infrastructure in Karachi, Pakistan.
  • 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_69ad8b187fc8819085914d3c9ea3142d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad99e12c5c8190af7cc20e4c48bf45 completed March 8, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b109061684819086777d3b871c94f8 completed March 11, 2026, 6:17 a.m.
NEDg Description generation batch_69b1196399e881908887513a3bdf7f98 completed March 11, 2026, 7:27 a.m.
NED2 Entity disambiguation (via description) batch_69b119d306208190b53b059f0ff57712 completed March 11, 2026, 7:29 a.m.
Created at: March 8, 2026, 2:59 p.m.