Triple

T9225166
Position Surface form Disambiguated ID Type / Status
Subject Bernau am Chiemsee E221662 entity
Predicate locatedNear P294 FINISHED
Object Rosenheim E69439 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: Rosenheim | Statement: [Bernau am Chiemsee, locatedNear, Rosenheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rosenheim
Context triple: [Bernau am Chiemsee, locatedNear, Rosenheim]
  • A. Rosenheim chosen
    Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
  • B. Traunstein
    Traunstein is a town in southeastern Bavaria, Germany, known as a regional administrative and cultural center near the Chiemsee and the Alps.
  • C. Eichstätt
    Eichstätt is a historic Bavarian town in southern Germany known for its baroque architecture, Catholic university, and location within the Altmühltal Nature Park.
  • D. Kempten
    Kempten is a historic town in Bavaria, Germany, considered one of the country’s oldest urban settlements and known for its location in the Allgäu region.
  • E. Kaufbeuren
    Kaufbeuren is a historic Bavarian town in southern Germany known for its well-preserved medieval old town and traditional Swabian culture.
  • 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_69ca83ec8db08190a9110df8232885d2 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccda9dbd1481909f35a4bee8e0b450 completed April 1, 2026, 8:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69d60d24c6dc819088332a512940a9c8 completed April 8, 2026, 8:09 a.m.
Created at: March 30, 2026, 7:28 p.m.