Triple

T5520818
Position Surface form Disambiguated ID Type / Status
Subject Wilhelm Groener E144801 entity
Predicate familyName P18 FINISHED
Object Groener
Groener is a German surname most notably associated with Wilhelm Groener, a prominent German general and politician during the early 20th century.
 E532449 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: Groener | Statement: [Wilhelm Groener, familyName, Groener]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Groener
Context triple: [Wilhelm Groener, familyName, Groener]
  • A. Gunten
    Gunten is a small lakeside village in the Swiss canton of Bern, known for its scenic location on the shores of Lake Thun in the Bernese Oberland.
  • B. Grünfier
    Grünfier is a small locality in the historical region of Pomerania, formerly part of Germany and now within modern-day Poland.
  • C. Goettsch
    Goettsch is a surname most prominently associated with the architecture firm Lohan Caprile Goettsch Architects and its architectural practice.
  • D. Oberhauser
    Oberhauser is a German-language surname borne by various notable individuals across fields such as sports, the arts, and public life.
  • E. Bramsche
    Bramsche is a town in Lower Saxony, Germany, known for its location near Osnabrück and its historical textile industry.
  • 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: Groener
Triple: [Wilhelm Groener, familyName, Groener]
Generated description
Groener is a German surname most notably associated with Wilhelm Groener, a prominent German general and politician during the early 20th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Groener
Target entity description: Groener is a German surname most notably associated with Wilhelm Groener, a prominent German general and politician during the early 20th century.
  • A. Gunten
    Gunten is a small lakeside village in the Swiss canton of Bern, known for its scenic location on the shores of Lake Thun in the Bernese Oberland.
  • B. Grünfier
    Grünfier is a small locality in the historical region of Pomerania, formerly part of Germany and now within modern-day Poland.
  • C. Goettsch
    Goettsch is a surname most prominently associated with the architecture firm Lohan Caprile Goettsch Architects and its architectural practice.
  • D. Oberhauser
    Oberhauser is a German-language surname borne by various notable individuals across fields such as sports, the arts, and public life.
  • E. Bramsche
    Bramsche is a town in Lower Saxony, Germany, known for its location near Osnabrück and its historical textile industry.
  • 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_69c008f873a481909b4d9f7e2db3c37d completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f7082ac8190a372fa75e8dec6a4 completed March 22, 2026, 4:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c027e995e88190833762cb94a781cc completed March 22, 2026, 5:33 p.m.
NEDg Description generation batch_69c03f8b6e948190870b98d6d69193fe completed March 22, 2026, 7:14 p.m.
NED2 Entity disambiguation (via description) batch_69c0404aedc08190a9b146466486be6e completed March 22, 2026, 7:17 p.m.
Created at: March 22, 2026, 3:33 p.m.