Triple

T3146768
Position Surface form Disambiguated ID Type / Status
Subject Fédération Française de Football E65782 entity
Predicate hasAbbreviation P43 FINISHED
Object FFF E18614 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: FFF | Statement: [Fédération Française de Football, hasAbbreviation, FFF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FFF
Context triple: [Fédération Française de Football, hasAbbreviation, FFF]
  • A. FFF chosen
    FFF is a global youth-led climate movement advocating for urgent action against climate change through school strikes and public demonstrations.
  • B. FFM
    FFM is an abbreviation commonly used for the Montreal World Film Festival, an international film festival held annually in Montreal, Canada.
  • C. FFS
    FFS is the commonly used abbreviation for the Swiss Federal Railways, the national railway company of Switzerland.
  • D. FFRRO
    FFRRO is a U.S. Environmental Protection Agency office that oversees the cleanup, restoration, and reuse of contaminated federal facilities such as military bases and government sites.
  • E. FFD
    FFD is the IATA airport code for RAF Fairford, a Royal Air Force station in Gloucestershire, England, used by both the UK and United States air forces and known for hosting major airshows.
  • 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_69ad8582f564819088c27e1f96153938 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada598ccf08190b8817c456f38f2d7 completed March 8, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69b235bad36c8190ab93312950380d36 completed March 12, 2026, 3:40 a.m.
Created at: March 8, 2026, 3:05 p.m.