Triple

T3715606
Position Surface form Disambiguated ID Type / Status
Subject Adolf Erik Nordenskiöld E81522 entity
Predicate placeOfDeath P21 FINISHED
Object Dalby, Scania
Dalby, Scania is a locality in southern Sweden known for its historic church and proximity to the city of Lund.
 E382696 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: Dalby, Scania | Statement: [Adolf Erik Nordenskiöld, placeOfDeath, Dalby, Scania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dalby, Scania
Context triple: [Adolf Erik Nordenskiöld, placeOfDeath, Dalby, Scania]
  • A. Dombås
    Dombås is a village in central Norway that serves as an important road and rail junction in the Gudbrandsdalen region and was a notable site of fighting during World War II.
  • B. Dalby
    Dalby is a rural town in Queensland, Australia, known as an agricultural and service hub on the Darling Downs.
  • C. Hjulsta
    Hjulsta is a suburb in northwestern Stockholm, Sweden, known for being the terminus of one of the Stockholm metro lines.
  • D. Hellebæk
    Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
  • E. Østerås
    Østerås is a suburban area in Bærum, Norway, best known as the western endpoint of one of the Oslo Metro lines.
  • 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: Dalby, Scania
Triple: [Adolf Erik Nordenskiöld, placeOfDeath, Dalby, Scania]
Generated description
Dalby, Scania is a locality in southern Sweden known for its historic church and proximity to the city of Lund.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dalby, Scania
Target entity description: Dalby, Scania is a locality in southern Sweden known for its historic church and proximity to the city of Lund.
  • A. Dombås
    Dombås is a village in central Norway that serves as an important road and rail junction in the Gudbrandsdalen region and was a notable site of fighting during World War II.
  • B. Dalby
    Dalby is a rural town in Queensland, Australia, known as an agricultural and service hub on the Darling Downs.
  • C. Hjulsta
    Hjulsta is a suburb in northwestern Stockholm, Sweden, known for being the terminus of one of the Stockholm metro lines.
  • D. Hellebæk
    Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
  • E. Østerås
    Østerås is a suburban area in Bærum, Norway, best known as the western endpoint of one of the Oslo Metro lines.
  • 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_69ad8b1a81588190b3f27a5483bb610e completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adc9cf77dc819098979094172d82d1 completed March 8, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4ce0f690c819091d9caf9271f9bbd completed March 14, 2026, 2:55 a.m.
NEDg Description generation batch_69b4cf6a84fc8190b07fbc31621bd871 completed March 14, 2026, 3 a.m.
NED2 Entity disambiguation (via description) batch_69b4d32caa7c81908332ac23bd4d9571 completed March 14, 2026, 3:17 a.m.
Created at: March 8, 2026, 3:33 p.m.