Triple

T12589292
Position Surface form Disambiguated ID Type / Status
Subject Leopold I, Duke of Lorraine E300558 entity
Predicate birthPlace P1 FINISHED
Object Innsbruck E110788 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: Innsbruck | Statement: [Leopold I, Duke of Lorraine, birthPlace, Innsbruck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Innsbruck
Context triple: [Leopold I, Duke of Lorraine, birthPlace, Innsbruck]
  • A. 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.
  • B. Salzburg
    Salzburg is a historic Austrian city on the Salzach River, renowned for its baroque architecture, Alpine setting, and as the birthplace of composer Wolfgang Amadeus Mozart.
  • C. Lenzburg
    Lenzburg is a historic Swiss town in the canton of Aargau, known for its medieval hilltop castle and well-preserved old town.
  • D. Bludenz
    Bludenz is a small alpine town in western Austria known as a regional hub for skiing, hiking, and chocolate production.
  • E. 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.
  • 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_69d7bde87b648190bcd0266e9efde098 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954bd5e8c8190a2f233b91682341f completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75464d85c8190a4c27f22cfd7dc96 completed May 3, 2026, 1:57 p.m.
Created at: April 9, 2026, 5:06 p.m.