Triple

T8227542
Position Surface form Disambiguated ID Type / Status
Subject Federal Social Court of Germany E192208 entity
Predicate hasAbbreviation P43 FINISHED
Object BSG E720536 NE FINISHED

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: BSG | Statement: [Federal Social Court of Germany, hasAbbreviation, BSG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BSG
Context triple: [Federal Social Court of Germany, hasAbbreviation, BSG]
  • A. BSG
    BSG is the IATA airport code for Bata Airport, serving the city of Bata in Equatorial Guinea.
  • B. BSG chosen
    BSG is the abbreviation for Germany’s Federal Social Court, the highest court for social law matters in the country.
  • C. SSBG
    SSBG is a federal funding program in the United States that provides flexible grants to states to support a wide range of social services for vulnerable populations.
  • D. BSA
    BSA (Birmingham Small Arms Company) was a major British manufacturer best known for producing firearms, military equipment, and later motorcycles and bicycles.
  • E. BSA
    BSA is a U.S. anti-money laundering law that requires financial institutions to assist government agencies in detecting and preventing financial crimes.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca82db5b90819085d1ad7c2e27bfcc completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb77fdcb048190868ea4995b020a37 completed March 31, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd67ec97348190a1ae7fc8d30af838 completed April 1, 2026, 6:46 p.m.
Created at: March 30, 2026, 5:46 p.m.