Triple

T19351858
Position Surface form Disambiguated ID Type / Status
Subject Regio E484040 entity
Predicate operatorAbbreviation P43 FINISHED
Object 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: FFS | Statement: [Regio, operatorAbbreviation, FFS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FFS
Context triple: [Regio, operatorAbbreviation, FFS]
  • A. FFS chosen
    FFS is the commonly used abbreviation for the Swiss Federal Railways, the national railway company of Switzerland.
  • B. FFS
    FFS is a high-performance file system originally developed for BSD Unix that introduced improved disk layout and efficiency over earlier Unix file systems.
  • C. FFS
    FFS is the station code for Frankfurt (Main) Süd, a major railway station in Frankfurt, Germany.
  • D. FFS
    FFS is the state agency responsible for managing and protecting Florida’s forest resources, including wildfire prevention, suppression, and sustainable forestry.
  • E. FFS
    FFS is the abbreviation for the Football Federation Samoa, the governing body responsible for overseeing football activities in Samoa.
  • 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_69d8e8d244f8819080eb1f3491300db2 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e61904a878819084d58ed3b7d8a978 completed April 20, 2026, 12:16 p.m.
Created at: April 10, 2026, 1:34 p.m.