Triple

T2136266
Position Surface form Disambiguated ID Type / Status
Subject Brandenburg E46660 entity
Predicate hasCity P316 FINISHED
Object Eberswalde
Eberswalde is a town in northeastern Germany known for its industrial heritage and surrounding forests, located northeast of Berlin.
E237109 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: Eberswalde | Statement: [Brandenburg, hasCity, Eberswalde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eberswalde
Context triple: [Brandenburg, hasCity, Eberswalde]
  • A. Neubukow
    Neubukow is a small town in northern Germany best known as the birthplace of archaeologist Heinrich Schliemann.
  • B. Maadi
    Maadi is a suburban district in southern Cairo, Egypt, known for its leafy residential streets, expatriate community, and proximity to the Nile.
  • C. Thale
    Thale is a small town in the northern Harz region of central Germany, known for its dramatic Bode Gorge, surrounding cliffs, and role as a gateway to popular hiking and nature areas.
  • D. Idstein
    Idstein is a historic town in the German state of Hesse, known for its well-preserved medieval old town and timber-framed architecture.
  • E. Lydenburg
    Lydenburg is a historic town in South Africa known for its early gold-mining heritage and proximity to scenic routes and nature reserves in the Mpumalanga province.
  • 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: Eberswalde
Triple: [Brandenburg, hasCity, Eberswalde]
Generated description
Eberswalde is a town in northeastern Germany known for its industrial heritage and surrounding forests, located northeast of Berlin.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Eberswalde
Target entity description: Eberswalde is a town in northeastern Germany known for its industrial heritage and surrounding forests, located northeast of Berlin.
  • A. Neubukow
    Neubukow is a small town in northern Germany best known as the birthplace of archaeologist Heinrich Schliemann.
  • B. Maadi
    Maadi is a suburban district in southern Cairo, Egypt, known for its leafy residential streets, expatriate community, and proximity to the Nile.
  • C. Thale
    Thale is a small town in the northern Harz region of central Germany, known for its dramatic Bode Gorge, surrounding cliffs, and role as a gateway to popular hiking and nature areas.
  • D. Idstein
    Idstein is a historic town in the German state of Hesse, known for its well-preserved medieval old town and timber-framed architecture.
  • E. Lydenburg
    Lydenburg is a historic town in South Africa known for its early gold-mining heritage and proximity to scenic routes and nature reserves in the Mpumalanga province.
  • 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_69a88a174ab48190a5db20c132e5dccf completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbdc4ce8c81908d143d5451681e6a completed March 7, 2026, 5:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae51acc0f88190a580e29d887170ec completed March 9, 2026, 4:50 a.m.
NEDg Description generation batch_69ae5322097c81909d77d54ae258ab1a completed March 9, 2026, 4:57 a.m.
NED2 Entity disambiguation (via description) batch_69ae5365cd808190aa8363b612ef0ec5 completed March 9, 2026, 4:58 a.m.
Created at: March 4, 2026, 7:44 p.m.