Triple

T561542
Position Surface form Disambiguated ID Type / Status
Subject Rhine E13461 entity
Predicate notableFeature P105 FINISHED
Object Middle Rhine Valley E60266 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: Middle Rhine Valley | Statement: [Rhine, notableFeature, Middle Rhine Valley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Middle Rhine Valley
Context triple: [Rhine, notableFeature, Middle Rhine Valley]
  • A. Rhône Valley
    The Rhône Valley is a major river valley in southeastern France renowned for its wine-producing regions, varied landscapes, and role as a key north–south transport corridor.
  • B. Hesse
    Hesse is a federal state in central Germany known for its financial hub Frankfurt am Main and its mix of urban centers, forests, and historic towns.
  • C. Black Forest
    The Black Forest is a large, densely wooded mountain range in southwestern Germany known for its picturesque villages, cuckoo clocks, and origin of the Danube River.
  • D. Basel-Landschaft
    Basel-Landschaft is a canton in northwestern Switzerland known for its proximity to Basel and its mix of industrial centers, suburban communities, and rural landscapes.
  • E. Rhineland chosen
    The Rhineland is a historically significant region in western Germany along the Rhine River, long contested as a strategic and economic heartland in European conflicts.
  • 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_69a4933edcf08190b35ecfd6014caee6 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a499e2795c8190903240e79964156d completed March 1, 2026, 7:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4e9bd6c44819094ba815966ca7937 completed March 2, 2026, 1:37 a.m.
Created at: March 1, 2026, 7:32 p.m.