Triple

T15438028
Position Surface form Disambiguated ID Type / Status
Subject Meschede E369819 entity
Predicate locatedNear P294 FINISHED
Object Warstein
Warstein is a town in North Rhine-Westphalia, Germany, best known for its Warsteiner brewery and its location in the Sauerland region.
 E1209742 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: Warstein | Statement: [Meschede, locatedNear, Warstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Warstein
Context triple: [Meschede, locatedNear, Warstein]
  • A. Ebermannstadt
    Ebermannstadt is a small historic town in northern Bavaria, Germany, known as a gateway to the scenic Franconian Switzerland region.
  • B. Staßfurt
    Staßfurt is a town in Saxony-Anhalt, Germany, historically known for its salt mining and chemical industry.
  • C. Tecklenburg
    Tecklenburg is a historic small town in North Rhine-Westphalia, Germany, known for its medieval architecture and open-air theater.
  • D. Fritzlar
    Fritzlar is a historic town in northern Hesse, Germany, known for its well-preserved medieval old town and its significance in early German Christian history.
  • E. Schwalmstadt
    Schwalmstadt is a small town in the Schwalm-Eder district of northern Hesse, Germany, known for its historic half-timbered architecture and picturesque setting in the Schwalm River valley.
  • 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: Warstein
Triple: [Meschede, locatedNear, Warstein]
Generated description
Warstein is a town in North Rhine-Westphalia, Germany, best known for its Warsteiner brewery and its location in the Sauerland region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Warstein
Target entity description: Warstein is a town in North Rhine-Westphalia, Germany, best known for its Warsteiner brewery and its location in the Sauerland region.
  • A. Ebermannstadt
    Ebermannstadt is a small historic town in northern Bavaria, Germany, known as a gateway to the scenic Franconian Switzerland region.
  • B. Staßfurt
    Staßfurt is a town in Saxony-Anhalt, Germany, historically known for its salt mining and chemical industry.
  • C. Tecklenburg
    Tecklenburg is a historic small town in North Rhine-Westphalia, Germany, known for its medieval architecture and open-air theater.
  • D. Fritzlar
    Fritzlar is a historic town in northern Hesse, Germany, known for its well-preserved medieval old town and its significance in early German Christian history.
  • E. Schwalmstadt
    Schwalmstadt is a small town in the Schwalm-Eder district of northern Hesse, Germany, known for its historic half-timbered architecture and picturesque setting in the Schwalm River valley.
  • 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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03edca064819081510bf303271062 completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0035450810819092796c556dfa8ed3 completed May 10, 2026, 7:35 a.m.
NEDg Description generation batch_6a0036111b54819096d62c61b8d4244d completed May 10, 2026, 7:38 a.m.
NED2 Entity disambiguation (via description) batch_6a00374fdecc819091f64e3174d013a6 completed May 10, 2026, 7:44 a.m.
Created at: April 10, 2026, 3:21 a.m.