Triple

T21579336
Position Surface form Disambiguated ID Type / Status
Subject Old Commandant's Headquarters E532483 entity
Predicate locatedInDistrict P40 FINISHED
Object Mitte
Mitte is the central district of Berlin, Germany, known for its historic landmarks, government buildings, and cultural institutions.
 E28609 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: Mitte | Statement: [Old Commandant's Headquarters, locatedInDistrict, Mitte]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mitte
Context triple: [Old Commandant's Headquarters, locatedInDistrict, Mitte]
  • A. Mitte
    Mitte is a central urban district of the German city of Koblenz, encompassing key administrative, commercial, and historic areas.
  • B. Mitte
    Mitte is the central urban district of Saarbrücken, Germany, encompassing much of the city’s administrative, commercial, and cultural core.
  • C. Mitte
    Mitte is the central district of Berlin, Germany, known as the historic core of the city and home to many major landmarks and government institutions.
  • D. Mitte
    Mitte is the central urban district of Ludwigshafen am Rhein, Germany, encompassing the city’s core commercial and administrative areas.
  • E. Mitte
    Mitte is a central district of the German town of Schwerte, typically encompassing its historic core and main administrative and commercial areas.
  • 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: Mitte
Triple: [Old Commandant's Headquarters, locatedInDistrict, Mitte]
Generated description
Mitte is the central district of Berlin, Germany, known for its historic landmarks, government buildings, and cultural institutions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mitte
Target entity description: Mitte is the central district of Berlin, Germany, known for its historic landmarks, government buildings, and cultural institutions.
  • A. Mitte chosen
    Mitte is the central district of Berlin, Germany, known as the historic core of the city and home to many major landmarks and government institutions.
  • B. Mitte
    Mitte is the central urban district of Ludwigshafen am Rhein, Germany, encompassing the city’s core commercial and administrative areas.
  • C. Mitte
    Mitte is a central urban district of the German city of Koblenz, encompassing key administrative, commercial, and historic areas.
  • D. Mitte
    Mitte is the central urban district of Saarbrücken, Germany, encompassing much of the city’s administrative, commercial, and cultural core.
  • E. Mitte
    Mitte is a central district of the German town of Schwerte, typically encompassing its historic core and main administrative and commercial areas.
  • F. None of above.

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_69e0c4618bec8190bcb0feb74568cbb1 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeeb5b8118819095fd751a03fbe8e8 completed April 27, 2026, 4:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09f67889bc81908d640cbe0bc4b121 completed May 17, 2026, 5:10 p.m.
NEDg Description generation batch_6a09f70d94308190b1c8f11e0a93b883 completed May 17, 2026, 5:12 p.m.
NED2 Entity disambiguation (via description) batch_6a09f7f91058819081d7230042ec080c completed May 17, 2026, 5:16 p.m.
Created at: April 16, 2026, 6:31 p.m.