Triple

T838397
Position Surface form Disambiguated ID Type / Status
Subject Gothenburg E18121 entity
Predicate demonym P191 FINISHED
Object Gothenburger
A Gothenburger is a resident or native of Gothenburg, Sweden’s second-largest city and a major port on the country’s west coast.
 E99026 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: Gothenburger | Statement: [Gothenburg, demonym, Gothenburger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gothenburger
Context triple: [Gothenburg, demonym, Gothenburger]
  • A. Goettsch
    Goettsch is a surname most prominently associated with the architecture firm Lohan Caprile Goettsch Architects and its architectural practice.
  • B. Fürth
    Fürth is a historic city in northern Bavaria, Germany, known for its well-preserved old town and proximity to Nuremberg within the Franconian metropolitan region.
  • C. Starnberg
    Starnberg is a lakeside town in Bavaria, Germany, known for its affluent residential character and scenic location on Lake Starnberg southwest of Munich.
  • D. Sorbs
    The Sorbs are a Slavic ethnic minority primarily living in eastern Germany, known for preserving their distinct Sorbian language and cultural traditions.
  • E. Cölln
    Cölln was a historic town on the River Spree that, together with Berlin, formed the core of what later became the city of Berlin.
  • 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: Gothenburger
Triple: [Gothenburg, demonym, Gothenburger]
Generated description
A Gothenburger is a resident or native of Gothenburg, Sweden’s second-largest city and a major port on the country’s west coast.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gothenburger
Target entity description: A Gothenburger is a resident or native of Gothenburg, Sweden’s second-largest city and a major port on the country’s west coast.
  • A. Goettsch
    Goettsch is a surname most prominently associated with the architecture firm Lohan Caprile Goettsch Architects and its architectural practice.
  • B. Fürth
    Fürth is a historic city in northern Bavaria, Germany, known for its well-preserved old town and proximity to Nuremberg within the Franconian metropolitan region.
  • C. Starnberg
    Starnberg is a lakeside town in Bavaria, Germany, known for its affluent residential character and scenic location on Lake Starnberg southwest of Munich.
  • D. Sorbs
    The Sorbs are a Slavic ethnic minority primarily living in eastern Germany, known for preserving their distinct Sorbian language and cultural traditions.
  • E. Cölln
    Cölln was a historic town on the River Spree that, together with Berlin, formed the core of what later became the city of Berlin.
  • 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_69a49389f44881909a608fb27d89f247 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4abd0e8bc8190afe29cd4745c2f86 completed March 1, 2026, 9:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7929624e88190bb7e1c644b8cc52b completed March 4, 2026, 2:01 a.m.
NEDg Description generation batch_69a793a3fa2481909cfdfd5825ee8e8d completed March 4, 2026, 2:06 a.m.
NED2 Entity disambiguation (via description) batch_69a794261614819089e8d36c7a0a94f1 completed March 4, 2026, 2:08 a.m.
Created at: March 1, 2026, 7:38 p.m.