Triple

T12727265
Position Surface form Disambiguated ID Type / Status
Subject Deputado Luís Eduardo Magalhães International Airport E304138 entity
Predicate IATAcode P418 FINISHED
Object SSA
SSA is the IATA airport code for Deputado Luís Eduardo Magalhães International Airport serving Salvador, Brazil.
 E1000510 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: SSA | Statement: [Deputado Luís Eduardo Magalhães International Airport, IATAcode, SSA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SSA
Context triple: [Deputado Luís Eduardo Magalhães International Airport, IATAcode, SSA]
  • 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 French Armed Forces Health Service, responsible for providing medical support and healthcare to military personnel in France and during overseas operations.
  • C. SSA
    SSA is the U.S. federal agency responsible for administering Social Security programs, including retirement, disability, and survivors benefits.
  • D. SSA
    SSA is the commonly used acronym for Mexico’s federal Secretariat of Health, the government ministry responsible for national public health policy and services.
  • E. SSA
    SSA is a major multi-purpose indoor arena in Saitama, Japan, known for hosting large-scale sports events, concerts, and entertainment shows.
  • 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: SSA
Triple: [Deputado Luís Eduardo Magalhães International Airport, IATAcode, SSA]
Generated description
SSA is the IATA airport code for Deputado Luís Eduardo Magalhães International Airport serving Salvador, Brazil.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SSA
Target entity description: SSA is the IATA airport code for Deputado Luís Eduardo Magalhães International Airport serving Salvador, Brazil.
  • A. SSA
    SSA is the U.S. federal agency responsible for administering Social Security programs, including retirement, disability, and survivors benefits.
  • B. SSA
    SSA is a professional scientific organization dedicated to advancing the study and understanding of earthquakes and seismic phenomena.
  • C. SSA
    SSA is the commonly used acronym for Mexico’s federal Secretariat of Health, the government ministry responsible for national public health policy and services.
  • D. SSA
    SSA is the French Armed Forces Health Service, responsible for providing medical support and healthcare to military personnel in France and during overseas operations.
  • E. SSA
    SSA is a major multi-purpose indoor arena in Saitama, Japan, known for hosting large-scale sports events, concerts, and entertainment shows.
  • 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_69d7bdf084148190ab9d513dc0735af4 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d964172490819080cd022ff8290b6e completed April 10, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c884bd08190bf0022e8303a4987 completed May 2, 2026, 10:36 p.m.
NEDg Description generation batch_69f67de172088190b055ace0fdcfd1fd completed May 2, 2026, 10:42 p.m.
NED2 Entity disambiguation (via description) batch_69f67ececce8819080335e67bd747057 completed May 2, 2026, 10:46 p.m.
Created at: April 9, 2026, 5:25 p.m.