Triple

T20706228
Position Surface form Disambiguated ID Type / Status
Subject Social Security Administration E508909 entity
Predicate abbreviation P43 FINISHED
Object SSA NE NERFINISHED

How this triple was built (2 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: [Social Security Administration, abbreviation, SSA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SSA
Context triple: [Social Security Administration, abbreviation, 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 chosen
    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 the IATA airport code for Deputado Luís Eduardo Magalhães International Airport serving Salvador, Brazil.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4c2b2a481909e31e9cb8f81ab55 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6c18fc8ec8190b020d540ae334c16 completed April 21, 2026, 12:15 a.m.
Created at: April 16, 2026, 12:13 p.m.