Triple

T3986939
Position Surface form Disambiguated ID Type / Status
Subject Defence Academy of the United Kingdom E86894 entity
Predicate abbreviation P43 FINISHED
Object DA
DA is the commonly used abbreviation for the Defence Academy of the United Kingdom, the institution responsible for advanced education and training of the UK’s armed forces and defence personnel.
 E404029 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: DA | Statement: [Defence Academy of the United Kingdom, abbreviation, DA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DA
Context triple: [Defence Academy of the United Kingdom, abbreviation, DA]
  • A. DA
    DA is the official abbreviation for the United States Department of the Army, the federal agency responsible for organizing, training, and equipping the U.S. Army.
  • B. DA
    DA is a postcode area in southeast England covering parts of south-east London and northwest Kent, including towns such as Dartford and Sidcup.
  • C. DAR
    DAR is the Philippine government agency responsible for implementing agrarian reform and redistributing agricultural land to farmers.
  • D. DAL
    DAL is the standard three-letter abbreviation used for the NHL team the Dallas Stars.
  • E. DAL
    DAL is the IATA airport code for Dallas Love Field, a major airport serving the Dallas, Texas area.
  • 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: DA
Triple: [Defence Academy of the United Kingdom, abbreviation, DA]
Generated description
DA is the commonly used abbreviation for the Defence Academy of the United Kingdom, the institution responsible for advanced education and training of the UK’s armed forces and defence personnel.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DA
Target entity description: DA is the commonly used abbreviation for the Defence Academy of the United Kingdom, the institution responsible for advanced education and training of the UK’s armed forces and defence personnel.
  • A. DA
    DA is the official abbreviation for the United States Department of the Army, the federal agency responsible for organizing, training, and equipping the U.S. Army.
  • B. DA
    DA is a postcode area in southeast England covering parts of south-east London and northwest Kent, including towns such as Dartford and Sidcup.
  • C. DAR
    DAR is the Philippine government agency responsible for implementing agrarian reform and redistributing agricultural land to farmers.
  • D. DAL
    DAL is the standard three-letter abbreviation used for the NHL team the Dallas Stars.
  • E. DAL
    DAL is the IATA airport code for Dallas Love Field, a major airport serving the Dallas, Texas area.
  • 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_69aed93fd9d4819085d3b2137d2346cb completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef9fe355081909b04662ab44fe2ca completed March 9, 2026, 4:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5402f72e8819097ce951aac465dc8 completed March 14, 2026, 11:02 a.m.
NEDg Description generation batch_69b54111e5188190ab8ec23124c22981 completed March 14, 2026, 11:05 a.m.
NED2 Entity disambiguation (via description) batch_69b54195261c8190a155b3c0469b0a35 completed March 14, 2026, 11:08 a.m.
Created at: March 9, 2026, 3:33 p.m.