Triple

T6019284
Position Surface form Disambiguated ID Type / Status
Subject Albert II of Hungary E134024 entity
Predicate country of citizenship P2 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: [Albert II of Hungary, country of citizenship, Austria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Austria
Context triple: [Albert II of Hungary, country of citizenship, 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. 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-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.
  • 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_69c008742a5c8190b9cb9c2787a3d8b3 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04f86efec8190bc357dddf6ebb4a9 completed March 22, 2026, 8:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1080a949c8190a9902f6da45e27a8 completed March 23, 2026, 9:29 a.m.
Created at: March 22, 2026, 4:07 p.m.