Triple

T2900194
Position Surface form Disambiguated ID Type / Status
Subject Service de santé des armées E62636 entity
Predicate shortName P43 FINISHED
Object 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.
 E307882 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: [Service de santé des armées, shortName, SSA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SSA
Context triple: [Service de santé des armées, shortName, 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 commonly used acronym for Mexico’s federal Secretariat of Health, the government ministry responsible for national public health policy and services.
  • C. SSA
    SSA is the U.S. federal agency responsible for administering Social Security programs, including retirement, disability, and survivors benefits.
  • D. SAA
    SAA is the ICAO airline designator for South African Airways, the flag carrier airline of South Africa.
  • E. SAS
    SAS is an elite special forces unit of the British Army renowned for its covert operations, counterterrorism expertise, and rigorous selection process.
  • 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: [Service de santé des armées, shortName, SSA]
Generated description
SSA is the French Armed Forces Health Service, responsible for providing medical support and healthcare to military personnel in France and during overseas operations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SSA
Target entity description: SSA is the French Armed Forces Health Service, responsible for providing medical support and healthcare to military personnel in France and during overseas operations.
  • 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. SAA
    SAA is the ICAO airline designator for South African Airways, the flag carrier airline of South Africa.
  • E. SAS
    SAS is an elite special forces unit of the British Army renowned for its covert operations, counterterrorism expertise, and rigorous selection process.
  • 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_69ab4c3e070c8190b78d3d2c005876dd completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abe0b081308190af8875151fb11c4e completed March 7, 2026, 8:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0318c544881909f6aabfb2d25e724 completed March 10, 2026, 2:58 p.m.
NEDg Description generation batch_69b038fdc7e881909dd0b6fd4f692e4a completed March 10, 2026, 3:30 p.m.
NED2 Entity disambiguation (via description) batch_69b03bca591c81908b3734cc8f2e712b completed March 10, 2026, 3:42 p.m.
Created at: March 6, 2026, 10:10 p.m.