Triple

T9099527
Position Surface form Disambiguated ID Type / Status
Subject Rheingau E218115 entity
Predicate wineLawRegionName P79500 FINISHED
Object Rheingau E218115 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: Rheingau | Statement: [Rheingau, wineLawRegionName, Rheingau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rheingau
Context triple: [Rheingau, wineLawRegionName, Rheingau]
  • A. Rheingau chosen
    Rheingau is a renowned German wine region along the Rhine River, especially famous for producing high-quality Riesling wines.
  • B. Schönbuch
    Schönbuch is a large forest and nature reserve in the German state of Baden-Württemberg, known for its extensive woodlands, wildlife, and recreational hiking areas.
  • C. Pfinz
    Pfinz is a river in Baden-Württemberg, Germany, that flows through the northern Black Forest region and the Karlsruhe area before joining the Enz.
  • D. Eschwege
    Eschwege is a small historic town in the German state of Hesse, known for its medieval architecture and location near the Werra River.
  • E. Oberweser
    Oberweser is the name given to the upper course of the Weser River in central Germany, encompassing its initial stretch after the confluence of its headstreams.
  • 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_69ca83d9844081908e561e367fda6d45 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc9710ac04819096b9c8d3399b9c35 completed April 1, 2026, 3:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69d030201a048190a3a1166d23c5ae67 completed April 3, 2026, 9:24 p.m.
Created at: March 30, 2026, 7:15 p.m.