Triple

T5744405
Position Surface form Disambiguated ID Type / Status
Subject Altmühl E126692 entity
Predicate flowsThrough P225 FINISHED
Object Gunzenhausen E118611 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: Gunzenhausen | Statement: [Altmühl, flowsThrough, Gunzenhausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gunzenhausen
Context triple: [Altmühl, flowsThrough, Gunzenhausen]
  • A. Gunzenhausen chosen
    Gunzenhausen is a historic town in Bavaria, Germany, known for its location on the Altmühl River and as a gateway to the Franconian Lake District.
  • B. Gunzesried
    Gunzesried is a small village in the Bavarian Alps of Germany, known for its picturesque mountain scenery and traditional alpine character.
  • C. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • D. Vellinghausen
    Vellinghausen is a village in western Germany known historically as the site of the Battle of Vellinghausen during the Seven Years' War.
  • E. Gernsbach
    Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
  • 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_69c0083179548190b384b0bf3c08ca4d completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c025883b608190b21523da2afde218 completed March 22, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c16e75b76c8190881ce6ec2d093925 completed March 23, 2026, 4:46 p.m.
Created at: March 22, 2026, 3:48 p.m.