Triple

T11775224
Position Surface form Disambiguated ID Type / Status
Subject Rat für deutsche Rechtschreibung E280000 entity
Predicate hasJurisdiction P285 FINISHED
Object Österreich E2895 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: Österreich | Statement: [Rat für deutsche Rechtschreibung, hasJurisdiction, Österreich]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Österreich
Context triple: [Rat für deutsche Rechtschreibung, hasJurisdiction, Österreich]
  • A. Austria chosen
    Austria is a landlocked Central European country known for its Alpine landscapes, rich cultural and musical heritage, and status as a prosperous, democratic member of the European Union.
  • B. Germany and Austria
    Germany and Austria are neighboring Central European countries that share historical, cultural, and linguistic ties, including a common use of the German language.
  • C. Austria and Hungary
    Austria and Hungary are neighboring Central European countries with closely linked histories, cultures, and transportation networks.
  • D. Austria and Slovakia
    Austria and Slovakia are neighboring Central European countries that share a border along the Morava River.
  • E. Styria
    Styria is a federal state in southeastern Austria known for its capital Graz, diverse landscapes, and strong industrial and educational sectors.
  • 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_69d6ab01d2688190ad8ed6bda487eaa5 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a55f415081908eec78cb2c956598 completed April 10, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f4580c9f7481908a45e6c098c06378 completed May 1, 2026, 7:36 a.m.
Created at: April 8, 2026, 9:41 p.m.