Triple

T4498718
Position Surface form Disambiguated ID Type / Status
Subject Werl E100762 entity
Predicate locatedNear P294 FINISHED
Object Soest plain
The Soest plain is a fertile lowland region in North Rhine-Westphalia, Germany, known for its intensive agriculture and historically significant settlement landscape.
E448070 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: Soest plain | Statement: [Werl, locatedNear, Soest plain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Soest plain
Context triple: [Werl, locatedNear, Soest plain]
  • A. Tivoli plain
    The Tivoli plain is a lowland area near the town of Tivoli in central Italy, known for its fertile terrain and historical significance in the Roman countryside.
  • B. Barnim Plateau
    The Barnim Plateau is a gently undulating glacial landscape in northeastern Germany, characterized by its morainic hills, forests, and agricultural areas.
  • C. Rottumerplaat
    Rottumerplaat is a small, uninhabited Dutch barrier island in the Wadden Sea, known for its protected nature reserve and birdlife.
  • D. Flachsland
    Flachsland is a German-language surname associated with individuals such as Maria Karoline Flachsland.
  • E. Dransfeld plateau
    The Dransfeld plateau is a hilly upland region in Lower Saxony, Germany, characterized by its forested landscapes and rural settlements.
  • 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: Soest plain
Triple: [Werl, locatedNear, Soest plain]
Generated description
The Soest plain is a fertile lowland region in North Rhine-Westphalia, Germany, known for its intensive agriculture and historically significant settlement landscape.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Soest plain
Target entity description: The Soest plain is a fertile lowland region in North Rhine-Westphalia, Germany, known for its intensive agriculture and historically significant settlement landscape.
  • A. Tivoli plain
    The Tivoli plain is a lowland area near the town of Tivoli in central Italy, known for its fertile terrain and historical significance in the Roman countryside.
  • B. Barnim Plateau
    The Barnim Plateau is a gently undulating glacial landscape in northeastern Germany, characterized by its morainic hills, forests, and agricultural areas.
  • C. Rottumerplaat
    Rottumerplaat is a small, uninhabited Dutch barrier island in the Wadden Sea, known for its protected nature reserve and birdlife.
  • D. Flachsland
    Flachsland is a German-language surname associated with individuals such as Maria Karoline Flachsland.
  • E. Dransfeld plateau
    The Dransfeld plateau is a hilly upland region in Lower Saxony, Germany, characterized by its forested landscapes and rural settlements.
  • 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_69bd43cdf15081909a4fa2585ff63b3e completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd56c29868819097633c7cd398e865 completed March 20, 2026, 2:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd6f89114081908adbd8e78d4c8ec4 completed March 20, 2026, 4:02 p.m.
NEDg Description generation batch_69bd71aecafc8190b0815d0308bbcaa9 completed March 20, 2026, 4:11 p.m.
NED2 Entity disambiguation (via description) batch_69bd75f39d788190b9e394050c55f44d completed March 20, 2026, 4:29 p.m.
Created at: March 20, 2026, 1 p.m.