Triple

T12446814
Position Surface form Disambiguated ID Type / Status
Subject Pattensen E297420 entity
Predicate hasSubdivision P747 FINISHED
Object Schulenburg
Schulenburg is a district-level locality within the town of Pattensen in Lower Saxony, Germany.
 E1014255 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: Schulenburg | Statement: [Pattensen, hasSubdivision, Schulenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Schulenburg
Context triple: [Pattensen, hasSubdivision, Schulenburg]
  • A. Siegsdorf
    Siegsdorf is a Bavarian town in southeastern Germany known for its scenic Alpine surroundings and proximity to the Chiemsee lake.
  • B. 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.
  • C. Judenburg
    Judenburg is a historic town in the Austrian state of Styria, known for its medieval architecture and former role as an important trading center.
  • D. Haslach
    Haslach is a district or locality that forms part of the town of Oberkirch in the German state of Baden-Württemberg.
  • E. Haslach
    Haslach is a town in southern Germany historically noted as the site of the Battle of Haslach-Jungingen during the Napoleonic Wars.
  • 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: Schulenburg
Triple: [Pattensen, hasSubdivision, Schulenburg]
Generated description
Schulenburg is a district-level locality within the town of Pattensen in Lower Saxony, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Schulenburg
Target entity description: Schulenburg is a district-level locality within the town of Pattensen in Lower Saxony, Germany.
  • A. Siegsdorf
    Siegsdorf is a Bavarian town in southeastern Germany known for its scenic Alpine surroundings and proximity to the Chiemsee lake.
  • B. 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.
  • C. Judenburg
    Judenburg is a historic town in the Austrian state of Styria, known for its medieval architecture and former role as an important trading center.
  • D. Haslach
    Haslach is a district or locality that forms part of the town of Oberkirch in the German state of Baden-Württemberg.
  • E. Haslach
    Haslach is a town in southern Germany historically noted as the site of the Battle of Haslach-Jungingen during the Napoleonic Wars.
  • 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_69d6ada166c48190b902972cd2408fa3 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d90f18c819083a36ff4b9be4a20 completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8bc820c8190b6e54a381621fdc8 completed May 3, 2026, 2:53 a.m.
NEDg Description generation batch_69f6b9dac2c88190850304023f156969 completed May 3, 2026, 2:58 a.m.
NED2 Entity disambiguation (via description) batch_69f6bb304f7c8190a02aa2c5f71cea89 completed May 3, 2026, 3:04 a.m.
Created at: April 8, 2026, 9:56 p.m.