Triple

T6712298
Position Surface form Disambiguated ID Type / Status
Subject Rosa Stradner E153174 entity
Predicate countryOfBirth P1 FINISHED
Object Austria 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: Austria | Statement: [Rosa Stradner, countryOfBirth, Austria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Austria
Context triple: [Rosa Stradner, countryOfBirth, Austria]
  • 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. Austria and Hungary
    Austria and Hungary are neighboring Central European countries with closely linked histories, cultures, and transportation networks.
  • C. 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.
  • D. Austria-Este
    Austria-Este is a cadet branch of the Habsburg-Lorraine dynasty that historically ruled the Duchy of Modena and Reggio and continues as a prominent European noble house.
  • E. Austria and Slovakia
    Austria and Slovakia are neighboring Central European countries that share a border along the Morava River.
  • 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_69c68808d8d8819087369015270788fe completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d108acc08190b38b43161d8912b9 completed March 27, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7007347cc8190a15b4218bb3b7074 completed March 27, 2026, 10:10 p.m.
Created at: March 27, 2026, 2:07 p.m.