Triple

T1839132
Position Surface form Disambiguated ID Type / Status
Subject Inn E41132 entity
Predicate majorCityOnRiver P316 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: [Inn, majorCityOnRiver, Rosenheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rosenheim
Context triple: [Inn, majorCityOnRiver, 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. 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.
  • D. Straubing
    Straubing is a Bavarian town on the Danube River known for its historic city center and role as a regional economic and educational hub.
  • E. Füssen
    Füssen is a picturesque Bavarian town in southern Germany, known for its historic old town, proximity to Neuschwanstein Castle, and scenic location near the Alps.
  • 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_69a88647f9388190909bc36e795bdaec completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb03b3eb08190ae68d8476fc89c7f completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69b57efde3148190ac7a0d94281a1ff2 completed March 14, 2026, 3:30 p.m.
Created at: March 4, 2026, 7:33 p.m.