Triple

T624976
Position Surface form Disambiguated ID Type / Status
Subject Reinickendorf E14596 entity
Predicate hasCityDistrict P2709 FINISHED
Object Lübars
Lübars is a historic, village-like district in Berlin’s Reinickendorf borough, known for its rural character, fields, and preserved traditional architecture within the city.
 E88245 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: Lübars | Statement: [Reinickendorf, hasCityDistrict, Lübars]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lübars
Context triple: [Reinickendorf, hasCityDistrict, Lübars]
  • A. Borsigwalde
    Borsigwalde is a residential locality in the Berlin borough of Reinickendorf, known for its industrial heritage linked to the Borsig engineering works.
  • B. Vian
    Vian is a surname most notably associated with British Royal Navy Admiral Philip Vian, who served with distinction during both World Wars.
  • C. Houffalize
    Houffalize is a small town in the Belgian Ardennes known for its World War II history, outdoor tourism, and scenic natural surroundings.
  • D. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • E. Brest
    Brest is a major port city in northwestern France that serves as one of the country’s principal naval and maritime centers.
  • 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: Lübars
Triple: [Reinickendorf, hasCityDistrict, Lübars]
Generated description
Lübars is a historic, village-like district in Berlin’s Reinickendorf borough, known for its rural character, fields, and preserved traditional architecture within the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lübars
Target entity description: Lübars is a historic, village-like district in Berlin’s Reinickendorf borough, known for its rural character, fields, and preserved traditional architecture within the city.
  • A. Borsigwalde
    Borsigwalde is a residential locality in the Berlin borough of Reinickendorf, known for its industrial heritage linked to the Borsig engineering works.
  • B. Vian
    Vian is a surname most notably associated with British Royal Navy Admiral Philip Vian, who served with distinction during both World Wars.
  • C. Houffalize
    Houffalize is a small town in the Belgian Ardennes known for its World War II history, outdoor tourism, and scenic natural surroundings.
  • D. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • E. Brest
    Brest is a major port city in northwestern France that serves as one of the country’s principal naval and maritime centers.
  • 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_69a4934b17c881909ace8270e8ddd202 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e43002c81908e0c7dab29b75978 completed March 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69a64a4ba2d88190969e7c777a1bbfd7 completed March 3, 2026, 2:41 a.m.
NEDg Description generation batch_69a64e773be08190abd15ff6ad35f37b completed March 3, 2026, 2:59 a.m.
NED2 Entity disambiguation (via description) batch_69a64edbfbe08190b49d26d572e3a484 completed March 3, 2026, 3 a.m.
Created at: March 1, 2026, 7:35 p.m.