Triple

T19620486
Position Surface form Disambiguated ID Type / Status
Subject Achensee E470991 entity
Predicate partOf P40 FINISHED
Object Innsbruck tourism region NE NERFINISHED

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: Innsbruck tourism region | Statement: [Achensee, partOf, Innsbruck tourism region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Innsbruck tourism region
Context triple: [Achensee, partOf, Innsbruck tourism region]
  • A. Igls
    Igls is an Austrian alpine village near Innsbruck known for its winter sports facilities and role in hosting Olympic events.
  • B. Innsbruck chosen
    Innsbruck is a city in western Austria known for its Alpine setting and winter sports facilities, and it later successfully hosted the Winter Olympics in 1964 and 1976.
  • C. Kufstein
    Kufstein is a historic town in the Austrian state of Tyrol, known for its medieval fortress and picturesque setting in the Alps near the German border.
  • D. Seefeld in Tirol
    Seefeld in Tirol is an Austrian alpine resort town renowned for its winter sports facilities and role as a host location for Olympic Nordic skiing events.
  • E. Zell am See
    Zell am See is a popular Austrian alpine town and lakeside resort known for its scenic mountain setting, skiing, and outdoor recreation.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e510fa248190b7afb274a1d4cf73 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e640e512d08190a76bf81b3282e0e5 completed April 20, 2026, 3:06 p.m.
Created at: April 10, 2026, 1:43 p.m.