Triple

T597020
Position Surface form Disambiguated ID Type / Status
Subject Federal Railroad Administration E11408 entity
Predicate abbreviation P43 FINISHED
Object FRA E11408 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: FRA | Statement: [Federal Railroad Administration, abbreviation, FRA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FRA
Context triple: [Federal Railroad Administration, abbreviation, FRA]
  • A. FRA
    FRA is the three-letter ISO 3166-1 alpha-3 country code that uniquely identifies France in international standards and data systems.
  • B. FRA chosen
    FRA is the United States government agency responsible for regulating and overseeing the nation’s railroad safety, infrastructure, and operations.
  • C. FRS
    FRS is the post-nominal title used by Fellows of the Royal Society, denoting distinguished scientists elected to the United Kingdom’s national academy of sciences.
  • D. FRB
    FRB is the commonly used abbreviation for the Federal Reserve Board of Governors, the central governing body of the U.S. Federal Reserve System that oversees national monetary policy and banking regulation.
  • E. FED
    FED is the commonly used abbreviation for the Fluids Engineering Division, a professional group focused on research and advancements in fluid mechanics and related technologies.
  • 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_69a4932779b881908688590d59c71900 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49d2b98d08190a1c1e8659efdfd75 completed March 1, 2026, 8:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69a518c766508190ae39b6e254a07bc3 completed March 2, 2026, 4:57 a.m.
Created at: March 1, 2026, 7:35 p.m.