Triple

T19423721
Position Surface form Disambiguated ID Type / Status
Subject French CFF E485925 entity
Predicate hasCounterpartAbbreviation P6587 FINISHED
Object Italian FFS 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: Italian FFS | Statement: [French CFF, hasCounterpartAbbreviation, Italian FFS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Italian FFS
Context triple: [French CFF, hasCounterpartAbbreviation, Italian FFS]
  • A. The Italian
    The Italian is a 1797 Gothic novel by Ann Radcliffe, renowned for its suspenseful plot, atmospheric settings, and exploration of religious and psychological themes.
  • B. Italo
    Italo is a masculine Italian given name historically borne by notable figures in politics, aviation, literature, and the arts.
  • C. Italo chosen
    Italo is a private Italian high-speed train operator known for connecting major cities across Italy with fast, modern rail services.
  • D. ITA
    ITA is the commonly used abbreviation for the Intercollegiate Tennis Association, the governing body for college tennis in the United States.
  • E. ITA
    ITA is the FIFA trigramme used to represent Italy in international football competitions.
  • 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_69d8e8d688f881909c85104a62e09d8a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e632169d9c81909a88704c6beb8fe0 completed April 20, 2026, 2:03 p.m.
Created at: April 10, 2026, 1:37 p.m.