Triple

T11768690
Position Surface form Disambiguated ID Type / Status
Subject Mondsee E279840 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Mondsee (market town) E945616 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: Mondsee (market town) | Statement: [Mondsee, hasNearbySettlement, Mondsee (market town)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mondsee (market town)
Context triple: [Mondsee, hasNearbySettlement, Mondsee (market town)]
  • A. town of Mondsee chosen
    The town of Mondsee is a picturesque Austrian lakeside settlement in Upper Austria, known for its historic abbey and scenic Alpine surroundings.
  • B. Obermarkt
    Obermarkt is a historic central market square in the city of Görlitz, Germany, known for its well-preserved architecture and role as a focal point of urban life.
  • C. Obermarkt
    Obermarkt is the historic main market square of Freiberg, known for its medieval architecture and central role in the city's public life.
  • D. Münklingen
    Münklingen is a village and district of the town Weil der Stadt in the German state of Baden-Württemberg.
  • E. Weiden am See
    Weiden am See is a small Austrian town in the state of Burgenland, known for its location on the shore of Lake Neusiedl and its wine-growing and tourism.
  • 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_69d6ab01d2688190ad8ed6bda487eaa5 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a526979c8190ad2089997906855b completed April 10, 2026, 7:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69f130b45ce081908669f4287961da7c completed April 28, 2026, 10:12 p.m.
Created at: April 8, 2026, 9:41 p.m.