Triple

T14170442
Position Surface form Disambiguated ID Type / Status
Subject Skellefteå E351191 entity
Predicate hasNickname P39 FINISHED
Object Guldstaden
Guldstaden is the Swedish nickname for Skellefteå, reflecting the town’s historic association with gold mining and prosperity.
 E1082959 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: Guldstaden | Statement: [Skellefteå, hasNickname, Guldstaden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Guldstaden
Context triple: [Skellefteå, hasNickname, Guldstaden]
  • A. Stålstaden
    Stålstaden is a Swedish city nickname referring to Eskilstuna’s historic role as a major steel and metalworking industrial center.
  • B. Guldhornene
    Guldhornene is a famous Romantic poem by Danish writer Adam Oehlenschläger that reflects on the loss of the ancient Golden Horns and the spiritual value of national heritage.
  • C. Grorud
    Grorud is a borough in the northeastern part of Oslo, Norway, known for its residential areas, green spaces, and diverse population.
  • D. Ergolding
    Ergolding is a market town in Lower Bavaria, Germany, situated just northeast of the city of Landshut along the Isar River.
  • E. Wisting
    Wisting is a Norwegian surname most notably borne by polar explorer Oscar Wisting, a key member of Roald Amundsen’s expeditions.
  • 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: Guldstaden
Triple: [Skellefteå, hasNickname, Guldstaden]
Generated description
Guldstaden is the Swedish nickname for Skellefteå, reflecting the town’s historic association with gold mining and prosperity.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Guldstaden
Target entity description: Guldstaden is the Swedish nickname for Skellefteå, reflecting the town’s historic association with gold mining and prosperity.
  • A. Stålstaden
    Stålstaden is a Swedish city nickname referring to Eskilstuna’s historic role as a major steel and metalworking industrial center.
  • B. Guldhornene
    Guldhornene is a famous Romantic poem by Danish writer Adam Oehlenschläger that reflects on the loss of the ancient Golden Horns and the spiritual value of national heritage.
  • C. Grorud
    Grorud is a borough in the northeastern part of Oslo, Norway, known for its residential areas, green spaces, and diverse population.
  • D. Ergolding
    Ergolding is a market town in Lower Bavaria, Germany, situated just northeast of the city of Landshut along the Isar River.
  • E. Wisting
    Wisting is a Norwegian surname most notably borne by polar explorer Oscar Wisting, a key member of Roald Amundsen’s expeditions.
  • 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_69d8278834a08190b0f1784e58d7b99c completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61b472288190b4a271daa54aa6cd completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcf7f779248190921c85f99f587296 completed May 7, 2026, 8:37 p.m.
NEDg Description generation batch_69fcf8bb58ac81908e66156a805edda8 completed May 7, 2026, 8:40 p.m.
NED2 Entity disambiguation (via description) batch_69fcf93b528c81908c0ee11908d25574 completed May 7, 2026, 8:42 p.m.
Created at: April 10, 2026, 1:01 a.m.