Triple

T15048205
Position Surface form Disambiguated ID Type / Status
Subject 2002 European floods E379285 entity
Predicate worstAffectedCity P107651 FINISHED
Object Passau E412680 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: Passau | Statement: [2002 European floods, worstAffectedCity, Passau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Passau
Context triple: [2002 European floods, worstAffectedCity, Passau]
  • A. Passau chosen
    Passau is a historic city in southeastern Germany, renowned for its picturesque old town and location at the meeting point of three rivers: the Danube, Inn, and Ilz.
  • B. 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.
  • C. Rosenheim
    Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
  • 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. Eichstätt
    Eichstätt is a historic Bavarian town in southern Germany known for its baroque architecture, Catholic university, and location within the Altmühltal Nature Park.
  • 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_69d85cd64d108190853797a95c11cc45 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69deda8e64e48190873104a02a676ff3 completed April 15, 2026, 12:23 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00a502c82881908d5b6f7c23e8a403 completed May 10, 2026, 3:32 p.m.
Created at: April 10, 2026, 3 a.m.