Triple

T4960734
Position Surface form Disambiguated ID Type / Status
Subject Grossglockner E111399 entity
Predicate highestPointOf P1674 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: [Grossglockner, highestPointOf, Austria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Austria
Context triple: [Grossglockner, highestPointOf, 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_69bd4419393c819086319a6fe4bf8542 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd71da80008190a0d606d5091822b8 completed March 20, 2026, 4:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69be92394f048190b6c0c87eea844f56 completed March 21, 2026, 12:42 p.m.
Created at: March 20, 2026, 1:32 p.m.