Triple

T2229962
Position Surface form Disambiguated ID Type / Status
Subject South African Airways E48741 entity
Predicate ICAOCode P419 FINISHED
Object SAA
SAA is the ICAO airline designator for South African Airways, the flag carrier airline of South Africa.
 E245437 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: SAA | Statement: [South African Airways, ICAOCode, SAA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SAA
Context triple: [South African Airways, ICAOCode, SAA]
  • A. SSA
    SSA is a professional scientific organization dedicated to advancing the study and understanding of earthquakes and seismic phenomena.
  • B. SSA
    SSA is the U.S. federal agency responsible for administering Social Security programs, including retirement, disability, and survivors benefits.
  • C. SA2
    SA2 is a 3GPP working group responsible for defining the overall system architecture and functional specifications of mobile communication networks.
  • D. SA3
    SA3 is the 3GPP security working group responsible for specifying and evolving security architecture and mechanisms across mobile communication standards.
  • E. SAU
    SAU is the three-letter ISO 3166-1 alpha-3 country code assigned to Saudi Arabia.
  • 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: SAA
Triple: [South African Airways, ICAOCode, SAA]
Generated description
SAA is the ICAO airline designator for South African Airways, the flag carrier airline of South Africa.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SAA
Target entity description: SAA is the ICAO airline designator for South African Airways, the flag carrier airline of South Africa.
  • A. SSA
    SSA is a professional scientific organization dedicated to advancing the study and understanding of earthquakes and seismic phenomena.
  • B. SSA
    SSA is the U.S. federal agency responsible for administering Social Security programs, including retirement, disability, and survivors benefits.
  • C. SA2
    SA2 is a 3GPP working group responsible for defining the overall system architecture and functional specifications of mobile communication networks.
  • D. SA3
    SA3 is the 3GPP security working group responsible for specifying and evolving security architecture and mechanisms across mobile communication standards.
  • E. SAU
    SAU is the three-letter ISO 3166-1 alpha-3 country code assigned to Saudi Arabia.
  • 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_69a88aa51b388190949868ec9766e587 completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc069e0ac8190bcda8cba9f5c7a5d completed March 7, 2026, 6:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae656a1f788190a08c3283bfedb6f4 completed March 9, 2026, 6:15 a.m.
NEDg Description generation batch_69ae65d4f26481909808c97b95ca9b30 completed March 9, 2026, 6:16 a.m.
NED2 Entity disambiguation (via description) batch_69ae6670b6d88190a09023fae63f4000 completed March 9, 2026, 6:19 a.m.
Created at: March 4, 2026, 7:47 p.m.