Triple

T18459711
Position Surface form Disambiguated ID Type / Status
Subject Rheinbach E450998 entity
Predicate hasSubdivision P747 FINISHED
Object Oberdrees NE NERFINISHED

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: Oberdrees | Statement: [Rheinbach, hasSubdivision, Oberdrees]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oberdrees
Context triple: [Rheinbach, hasSubdivision, Oberdrees]
  • A. Oberdrees chosen
    Oberdrees is a village-level district of the town of Rheinbach in the Rhein-Sieg-Kreis of North Rhine-Westphalia, Germany.
  • B. Reißeck
    Reißeck is a municipality in the Austrian state of Carinthia, known for its Alpine landscape and proximity to the Reißeck mountain range and hydroelectric facilities.
  • C. Weisselberg
    Weisselberg is a surname most prominently associated with Allen Weisselberg, the longtime chief financial officer of the Trump Organization.
  • D. Degerloch
    Degerloch is a district of Stuttgart in the German state of Baden-Württemberg, known for its elevated location and residential character.
  • E. Oßling
    Oßling is a small municipality in the German state of Saxony, located in the eastern part of the country.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38345688190b565eac2e4cd7935 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e52a7cdb5c8190a399f0e4052f7d1f completed April 19, 2026, 7:18 p.m.
Created at: April 10, 2026, 11:33 a.m.