Triple

T19492499
Position Surface form Disambiguated ID Type / Status
Subject Baar region E487685 entity
Predicate administrativeRegion P285 FINISHED
Object Tuttlingen district (partly) NE NERFINISHED

How this triple was built (3 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: Tuttlingen district (partly) | Statement: [Baar region, administrativeRegion, Tuttlingen district (partly)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tuttlingen district (partly)
Context triple: [Baar region, administrativeRegion, Tuttlingen district (partly)]
  • A. Reutlingen district
    Reutlingen district is an administrative district (Landkreis) in the state of Baden-Württemberg in southwestern Germany, known for its mix of industrial towns and scenic Swabian Alb landscapes.
  • B. Biberach district
    Biberach district is a rural administrative district in the state of Baden-Württemberg in southern Germany, known for its historic towns and location in the Upper Swabia region.
  • C. Rastatt district
    Rastatt district is an administrative district (Landkreis) in the state of Baden-Württemberg in southwestern Germany, located near the Black Forest and the Upper Rhine.
  • D. Waldshut district
    Waldshut district is an administrative district (Landkreis) in the state of Baden-Württemberg in southwestern Germany, located along the Upper Rhine on the Swiss border.
  • E. Miesbach district
    Miesbach district is a rural administrative district in Upper Bavaria, Germany, known for its Alpine landscapes, lakes, and popular tourist destinations.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tuttlingen district (partly)
Target entity description: Tuttlingen district is a rural administrative district in the state of Baden-Württemberg in southwestern Germany, known for its strong medical technology industry and location along the upper Danube River.
  • A. Reutlingen district
    Reutlingen district is an administrative district (Landkreis) in the state of Baden-Württemberg in southwestern Germany, known for its mix of industrial towns and scenic Swabian Alb landscapes.
  • B. Biberach district
    Biberach district is a rural administrative district in the state of Baden-Württemberg in southern Germany, known for its historic towns and location in the Upper Swabia region.
  • C. Rastatt district
    Rastatt district is an administrative district (Landkreis) in the state of Baden-Württemberg in southwestern Germany, located near the Black Forest and the Upper Rhine.
  • D. Waldshut district
    Waldshut district is an administrative district (Landkreis) in the state of Baden-Württemberg in southwestern Germany, located along the Upper Rhine on the Swiss border.
  • E. Miesbach district
    Miesbach district is a rural administrative district in Upper Bavaria, Germany, known for its Alpine landscapes, lakes, and popular tourist destinations.
  • F. None of above. chosen

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_69d8e8d9d1c88190b01cd78b8be49384 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6348f4d708190a6e612863fee4b97 completed April 20, 2026, 2:13 p.m.
Created at: April 10, 2026, 1:39 p.m.