Triple

T13691403
Position Surface form Disambiguated ID Type / Status
Subject Unterallgäu E328272 entity
Predicate neighboringDistrict P17964 FINISHED
Object Günzburg E273207 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: Günzburg | Statement: [Unterallgäu, neighboringDistrict, Günzburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Günzburg
Context triple: [Unterallgäu, neighboringDistrict, Günzburg]
  • A. Günzburg chosen
    Günzburg is a small Bavarian town in southern Germany, historically notable as the birthplace of Nazi physician Josef Mengele.
  • B. Kaufbeuren
    Kaufbeuren is a historic Bavarian town in southern Germany known for its well-preserved medieval old town and traditional Swabian culture.
  • 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. Wolfratshausen
    Wolfratshausen is a Bavarian town in southern Germany known for its historic old town, riverside setting on the Loisach and Isar, and proximity to Munich and the Alps.
  • E. Haßfurt
    Haßfurt is a small town in northern Bavaria, Germany, situated on the Main River and known for its historic architecture and regional administrative role.
  • 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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc8746458819095ec1ba3c01ef31b completed April 12, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb6e3d048190869bba1b4a7e255f completed May 8, 2026, 3:04 p.m.
Created at: April 9, 2026, 9:53 p.m.