Triple

T5556588
Position Surface form Disambiguated ID Type / Status
Subject Weilburg E145657 entity
Predicate hasTwinTown P919 FINISHED
Object Löwenberg
Löwenberg is a town in Germany known for its cultural and municipal partnership as a twin town of Weilburg.
 E533437 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: Löwenberg | Statement: [Weilburg, hasTwinTown, Löwenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Löwenberg
Context triple: [Weilburg, hasTwinTown, Löwenberg]
  • A. Bromberg
    Bromberg is the former German name for the city of Bydgoszcz, a major urban and industrial center in present-day north-central Poland.
  • B. Biesenthal
    Biesenthal is a small town in the Barnim district of Brandenburg, Germany, known for its surrounding lakes, forests, and location within the Barnim Nature Park.
  • C. Luxenberg
    Luxenberg is an alternative spelling or variant form of the name "Luxemburg," which can refer to the European country Luxembourg or the surname of notable individuals such as revolutionary Rosa Luxemburg.
  • D. Neubukow
    Neubukow is a small town in northern Germany best known as the birthplace of archaeologist Heinrich Schliemann.
  • E. Löwenstein
    Löwenstein is the original family name of the renowned Hungarian-American actor Peter Lorre, known for his distinctive roles in classic Hollywood and European cinema.
  • 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: Löwenberg
Triple: [Weilburg, hasTwinTown, Löwenberg]
Generated description
Löwenberg is a town in Germany known for its cultural and municipal partnership as a twin town of Weilburg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Löwenberg
Target entity description: Löwenberg is a town in Germany known for its cultural and municipal partnership as a twin town of Weilburg.
  • A. Bromberg
    Bromberg is the former German name for the city of Bydgoszcz, a major urban and industrial center in present-day north-central Poland.
  • B. Biesenthal
    Biesenthal is a small town in the Barnim district of Brandenburg, Germany, known for its surrounding lakes, forests, and location within the Barnim Nature Park.
  • C. Luxenberg
    Luxenberg is an alternative spelling or variant form of the name "Luxemburg," which can refer to the European country Luxembourg or the surname of notable individuals such as revolutionary Rosa Luxemburg.
  • D. Neubukow
    Neubukow is a small town in northern Germany best known as the birthplace of archaeologist Heinrich Schliemann.
  • E. Löwenstein
    Löwenstein is the original family name of the renowned Hungarian-American actor Peter Lorre, known for his distinctive roles in classic Hollywood and European cinema.
  • 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_69c008fcaf788190bafa02a1917ee73b completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01ffc5e7c81908e1c454d3bfd357b completed March 22, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0283bd408819085c62caf254df339 completed March 22, 2026, 5:34 p.m.
NEDg Description generation batch_69c03d668fe88190a1cf88b0708b405f completed March 22, 2026, 7:05 p.m.
NED2 Entity disambiguation (via description) batch_69c03de30928819094af492af0281130 completed March 22, 2026, 7:07 p.m.
Created at: March 22, 2026, 3:36 p.m.