Triple

T9814768
Position Surface form Disambiguated ID Type / Status
Subject Ingelheim am Rhein E238373 entity
Predicate hasPart P35 FINISHED
Object Nieder-Ingelheim E238373 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: Nieder-Ingelheim | Statement: [Ingelheim am Rhein, hasPart, Nieder-Ingelheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nieder-Ingelheim
Context triple: [Ingelheim am Rhein, hasPart, Nieder-Ingelheim]
  • A. Ingelheim am Rhein chosen
    Ingelheim am Rhein is a town in western Germany on the Rhine River, known historically as an imperial residence of Charlemagne and today for its wine production and pharmaceutical industry.
  • B. Uerdingen
    Uerdingen is a district of the German city of Krefeld, known historically for its chemical industry and location along the Rhine River.
  • C. Badenweiler
    Badenweiler is a spa town in southwestern Germany’s Black Forest region, known for its thermal baths and as the place where Russian writer Anton Chekhov died.
  • D. Bruchsal
    Bruchsal is a town in the state of Baden-Württemberg in southwestern Germany, known for its baroque palace and asparagus cultivation.
  • E. Weilburg
    Weilburg is a historic town in the German state of Hesse, known for its Renaissance castle and as the ancestral seat of the House of Nassau-Weilburg.
  • 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_69ca84dfde1481909f47c286d715f892 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb2f19660819083e3f15780352052 completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc67db68819093217c9a74e72fbf completed April 5, 2026, 2:43 a.m.
Created at: March 30, 2026, 8:30 p.m.