Triple

T8283392
Position Surface form Disambiguated ID Type / Status
Subject Fortuna Düsseldorf E193732 entity
Predicate hasAbbreviation P43 FINISHED
Object F95 E723404 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: F95 | Statement: [Fortuna Düsseldorf, hasAbbreviation, F95]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: F95
Context triple: [Fortuna Düsseldorf, hasAbbreviation, F95]
  • A. F95 chosen
    F95 is a common nickname for Fortuna Düsseldorf, a German football club based in Düsseldorf that competes in the country’s professional league system.
  • B. FH9
    FH9 is a proprietary vector graphics file format associated with Macromedia FreeHand version 9, used for storing illustrations and design layouts.
  • C. K95
    K95 is a ski jumping hill size classification indicating a normal hill with a K-point of 95 meters, commonly used in competitive ski jumping events.
  • D. C595
    C595 is the designation for an ASTM standard specification covering blended hydraulic cements used in construction.
  • E. FR-90
    FR-90 is the ISO 3166-2 subdivision code assigned to the Territoire de Belfort department in northeastern France.
  • 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_69ca82e217a48190880695635c44b2ed completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7aceec8881909cdfa488dfedc0f5 completed March 31, 2026, 7:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd952399dc8190914951d4e9e36c38 completed April 1, 2026, 9:58 p.m.
Created at: March 30, 2026, 5:52 p.m.