Triple

T7782633
Position Surface form Disambiguated ID Type / Status
Subject Saale-Holzland-Kreis E221559 entity
Predicate contains P35 FINISHED
Object Orlamünde
Orlamünde is a small historic town in the German state of Thuringia, situated along the Saale River.
 E693405 NE FINISHED

How this triple was built (4 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: Orlamünde | Statement: [Saale-Holzland-Kreis, contains, Orlamünde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Orlamünde
Context triple: [Saale-Holzland-Kreis, contains, Orlamünde]
  • A. Flerzheim
    Flerzheim is a village and district of the town of Rheinbach in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
  • B. Kamperland
    Kamperland is a village in the Dutch province of Zeeland, located on the island of Noord-Beveland and known as a coastal and recreational destination.
  • C. Őrség
    Őrség is a scenic, sparsely populated region in western Hungary known for its traditional villages, rolling landscapes, and preserved natural and cultural heritage.
  • D. Blautal
    Blautal is a scenic valley in Baden-Württemberg, Germany, shaped by the river Blau and known for its karst landscapes and picturesque towns.
  • E. Pays d’Olmes
    Pays d’Olmes is a small mountainous area in the Ariège department of southwestern France, known for its textile heritage and proximity to the Pyrenees.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Orlamünde
Triple: [Saale-Holzland-Kreis, contains, Orlamünde]
Generated description
Orlamünde is a small historic town in the German state of Thuringia, situated along the Saale River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Orlamünde
Target entity description: Orlamünde is a small historic town in the German state of Thuringia, situated along the Saale River.
  • A. Flerzheim
    Flerzheim is a village and district of the town of Rheinbach in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
  • B. Kamperland
    Kamperland is a village in the Dutch province of Zeeland, located on the island of Noord-Beveland and known as a coastal and recreational destination.
  • C. Őrség
    Őrség is a scenic, sparsely populated region in western Hungary known for its traditional villages, rolling landscapes, and preserved natural and cultural heritage.
  • D. Blautal
    Blautal is a scenic valley in Baden-Württemberg, Germany, shaped by the river Blau and known for its karst landscapes and picturesque towns.
  • E. Pays d’Olmes
    Pays d’Olmes is a small mountainous area in the Ariège department of southwestern France, known for its textile heritage and proximity to the Pyrenees.
  • F. None of above. chosen

Provenance (5 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_69ca83ebbef881909ac47f789145fef7 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cadf1f9c648190ac2b06d0d54035ea completed March 30, 2026, 8:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69caf5e400d881909d6cdeb7eaac3a59 completed March 30, 2026, 10:15 p.m.
NEDg Description generation batch_69caf81ebde881909bd131da8987b449 completed March 30, 2026, 10:24 p.m.
NED2 Entity disambiguation (via description) batch_69cafa013f348190a2067dee4a0c8c40 completed March 30, 2026, 10:32 p.m.
Created at: March 30, 2026, 4:21 p.m.