Triple

T15852580
Position Surface form Disambiguated ID Type / Status
Subject Sudanese Air Force E384376 entity
Predicate abbreviation P43 FINISHED
Object SuAF
SuAF is the acronym commonly used for the Sudanese Air Force, the aerial warfare branch of Sudan’s military.
 E1179395 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: SuAF | Statement: [Sudanese Air Force, abbreviation, SuAF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SuAF
Context triple: [Sudanese Air Force, abbreviation, SuAF]
  • A. TuAF
    TuAF is the commonly used abbreviation for the Turkish Air Force, the aerial warfare branch of Turkey’s armed forces.
  • B. SAU
    SAU is the three-letter ISO 3166-1 alpha-3 country code assigned to Saudi Arabia.
  • C. SAU
    SAU is an international university established by the South Asian Association for Regional Cooperation (SAARC) in New Delhi, India, focusing on postgraduate and doctoral education and research for students from South Asian countries.
  • D. USAFAS
    USAFAS is an acronym that most commonly refers to a United States Air Force–related organization, such as a school, squadron, or support unit, depending on context.
  • E. USAFAS
    USAFAS is the United States Army’s primary training and doctrine institution for field artillery officers and soldiers.
  • 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: SuAF
Triple: [Sudanese Air Force, abbreviation, SuAF]
Generated description
SuAF is the acronym commonly used for the Sudanese Air Force, the aerial warfare branch of Sudan’s military.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SuAF
Target entity description: SuAF is the acronym commonly used for the Sudanese Air Force, the aerial warfare branch of Sudan’s military.
  • A. TuAF
    TuAF is the commonly used abbreviation for the Turkish Air Force, the aerial warfare branch of Turkey’s armed forces.
  • B. SAU
    SAU is the three-letter ISO 3166-1 alpha-3 country code assigned to Saudi Arabia.
  • C. SAU
    SAU is an international university established by the South Asian Association for Regional Cooperation (SAARC) in New Delhi, India, focusing on postgraduate and doctoral education and research for students from South Asian countries.
  • D. USAFAS
    USAFAS is an acronym that most commonly refers to a United States Air Force–related organization, such as a school, squadron, or support unit, depending on context.
  • E. USAFAS
    USAFAS is the United States Army’s primary training and doctrine institution for field artillery officers and soldiers.
  • 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_69d86da422088190aac39e32e6c68429 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e14caddd2c8190859b2926b0e1ad35 completed April 16, 2026, 8:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa147bce481909fb6f6ef2793a5a8 completed May 9, 2026, 9:04 p.m.
NEDg Description generation batch_69ffa41a86ec8190b46d541965ecf26e completed May 9, 2026, 9:16 p.m.
NED2 Entity disambiguation (via description) batch_69ffa496f3e48190b8dc82bece548aec completed May 9, 2026, 9:18 p.m.
Created at: April 10, 2026, 4:50 a.m.