Triple

T5724699
Position Surface form Disambiguated ID Type / Status
Subject Swiss Federal Railways network E126235 entity
Predicate abbreviation P43 FINISHED
Object CFF network E112374 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: CFF network | Statement: [Swiss Federal Railways network, abbreviation, CFF network]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CFF network
Context triple: [Swiss Federal Railways network, abbreviation, CFF network]
  • A. CFF chosen
    CFF is the French-language abbreviation for the Swiss Federal Railways, the national railway company of Switzerland.
  • B. FFC
    FFC is the common abbreviation for Fluminense Football Club, a traditional Brazilian sports club best known for its professional football team based in Rio de Janeiro.
  • C. FFC
    FFC is the commonly used abbreviation for Falkirk Football Club, a professional Scottish football team based in Falkirk.
  • D. CCCF
    CCCF was a former regional football confederation in Central America and the Caribbean that governed the sport before being merged into CONCACAF.
  • E. CCFC
    CCFC is the commonly used abbreviation for Cardiff City Football Club, a professional football team based in Cardiff, Wales.
  • 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_69c0082f723881908ce8bb13a0c0f8b7 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c025085f508190adf5d540bc8a5b1c completed March 22, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a83c88c819097abe565ba010a29 completed March 22, 2026, 9:09 p.m.
Created at: March 22, 2026, 3:47 p.m.