Triple

T1848263
Position Surface form Disambiguated ID Type / Status
Subject Ammersee E41332 entity
Predicate hasSettlementOnShore P16159 FINISHED
Object Utting am Ammersee E206211 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: Utting am Ammersee | Statement: [Ammersee, hasSettlementOnShore, Utting am Ammersee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Utting am Ammersee
Context triple: [Ammersee, hasSettlementOnShore, Utting am Ammersee]
  • A. Prien am Chiemsee
    Prien am Chiemsee is a Bavarian market town in southern Germany known as a popular lakeside resort and gateway to the Chiemsee islands.
  • B. Dießen am Ammersee chosen
    Dießen am Ammersee is a Bavarian market town in southern Germany known for its lakeside setting, historic monastery, and role as a cultural and recreational center on the Ammersee.
  • C. Ammersee
    Ammersee is a large glacial lake in southern Germany known for its scenic shores, recreational activities, and proximity to the Alps.
  • D. Bad Waldsee
    Bad Waldsee is a historic spa town in the German state of Baden-Württemberg, known for its thermal baths and picturesque old town.
  • E. Starnberger See
    Starnberger See is a large, scenic lake in southern Germany known for its affluent lakeside communities, recreational activities, and historical associations with Bavarian royalty.
  • 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_69a88648cd44819093303206d96d76ad completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb7c2354081909ee4da7669932796 completed March 7, 2026, 5:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69add1c6941081909cef987ebe4b4d6c completed March 8, 2026, 7:45 p.m.
Created at: March 4, 2026, 7:33 p.m.