Triple

T1333955
Position Surface form Disambiguated ID Type / Status
Subject Bernhard von Galen E28704 entity
Predicate birthPlace P1 FINISHED
Object Drensteinfurt
Drensteinfurt is a small town in North Rhine-Westphalia, Germany, known for its historic architecture and location in the Münsterland region.
E210296 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: Drensteinfurt | Statement: [Bernhard von Galen, birthPlace, Drensteinfurt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Drensteinfurt
Context triple: [Bernhard von Galen, birthPlace, Drensteinfurt]
  • A. Heidenheim an der Brenz
    Heidenheim an der Brenz is a town in the German state of Baden-Württemberg known for its industrial heritage, historic castle Hellenstein, and location on the Brenz River near the Swabian Jura.
  • B. Schwandorf
    Schwandorf is a town in the Upper Palatinate region of Bavaria, Germany, known as a local administrative and commercial center on the Naab River.
  • C. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • D. Hubersdorf
    Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
  • E. Tureberg
    Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
  • 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: Drensteinfurt
Triple: [Bernhard von Galen, birthPlace, Drensteinfurt]
Generated description
Drensteinfurt is a small town in North Rhine-Westphalia, Germany, known for its historic architecture and location in the Münsterland region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Drensteinfurt
Target entity description: Drensteinfurt is a small town in North Rhine-Westphalia, Germany, known for its historic architecture and location in the Münsterland region.
  • A. Heidenheim an der Brenz
    Heidenheim an der Brenz is a town in the German state of Baden-Württemberg known for its industrial heritage, historic castle Hellenstein, and location on the Brenz River near the Swabian Jura.
  • B. Schwandorf
    Schwandorf is a town in the Upper Palatinate region of Bavaria, Germany, known as a local administrative and commercial center on the Naab River.
  • C. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • D. Hubersdorf
    Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
  • E. Tureberg
    Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
  • 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_69a498561a508190a3e1bc137c2b866a completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c1e98900819092c54c0fb58b958a completed March 1, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69addf2374ac8190ac2a2a753c056a3d completed March 8, 2026, 8:42 p.m.
NEDg Description generation batch_69ade16fdfdc81908299c6bf1fd973d8 completed March 8, 2026, 8:52 p.m.
NED2 Entity disambiguation (via description) batch_69ade1b832fc81908bd9ab364cd333c7 completed March 8, 2026, 8:53 p.m.
Created at: March 1, 2026, 7:55 p.m.