Triple

T9399032
Position Surface form Disambiguated ID Type / Status
Subject Daniel Solander E226419 entity
Predicate birthPlace P1 FINISHED
Object Piteå
Piteå is a coastal town in northern Sweden known for its historic wooden architecture, archipelago, and role as a regional cultural and industrial center in Norrbotten County.
 E797170 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: Piteå | Statement: [Daniel Solander, birthPlace, Piteå]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Piteå
Context triple: [Daniel Solander, birthPlace, Piteå]
  • A. Pajala
    Pajala is a small town in northern Sweden’s Lapland region, known for its remote Arctic setting and as the backdrop of several works by author Mikael Niemi.
  • B. Luleå
    Luleå is a coastal city in northern Sweden known for its major port, technology and university hub, and proximity to the Arctic Circle.
  • C. Gällivare
    Gällivare is a mining town in northern Sweden known for its significant iron ore deposits and role in the region’s mining industry.
  • D. Haparanda
    Haparanda is a small Swedish town on the border with Finland, known as a key cross-border trading hub and the easternmost town in Sweden.
  • E. Umeå
    Umeå is a university city in northern Sweden known for its cultural scene, research institutions, and role as a regional economic hub.
  • 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: Piteå
Triple: [Daniel Solander, birthPlace, Piteå]
Generated description
Piteå is a coastal town in northern Sweden known for its historic wooden architecture, archipelago, and role as a regional cultural and industrial center in Norrbotten County.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Piteå
Target entity description: Piteå is a coastal town in northern Sweden known for its historic wooden architecture, archipelago, and role as a regional cultural and industrial center in Norrbotten County.
  • A. Pajala
    Pajala is a small town in northern Sweden’s Lapland region, known for its remote Arctic setting and as the backdrop of several works by author Mikael Niemi.
  • B. Luleå
    Luleå is a coastal city in northern Sweden known for its major port, technology and university hub, and proximity to the Arctic Circle.
  • C. Gällivare
    Gällivare is a mining town in northern Sweden known for its significant iron ore deposits and role in the region’s mining industry.
  • D. Haparanda
    Haparanda is a small Swedish town on the border with Finland, known as a key cross-border trading hub and the easternmost town in Sweden.
  • E. Umeå
    Umeå is a university city in northern Sweden known for its cultural scene, research institutions, and role as a regional economic hub.
  • 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_69ca843170f88190800a8ab2b5fc568e completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd51556fc08190b8ff8190a1485a3a completed April 1, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1079798048190a1bd5318df4b1649 completed April 4, 2026, 12:44 p.m.
NEDg Description generation batch_69d1082f41b48190b8588bb986028f59 completed April 4, 2026, 12:46 p.m.
NED2 Entity disambiguation (via description) batch_69d108bab8c881909748ffbb4b23f4ba completed April 4, 2026, 12:48 p.m.
Created at: March 30, 2026, 7:46 p.m.