Triple

T11041637
Position Surface form Disambiguated ID Type / Status
Subject Ernst Happel E261030 entity
Predicate workLocation P7 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: [Ernst Happel, workLocation, Austria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Austria
Context triple: [Ernst Happel, workLocation, 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_69d6aa979bdc8190bf0e79104cc098c1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7980050948190ae7b187da5b776ca completed April 9, 2026, 12:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3c80ada908190a244eccc2b48df60 completed April 18, 2026, 6:06 p.m.
Created at: April 8, 2026, 9:26 p.m.