Triple

T1037345
Position Surface form Disambiguated ID Type / Status
Subject Kemi E22392 entity
Predicate twinTown P1072 FINISHED
Object Luleå
Luleå is a coastal city in northern Sweden known for its major port, technology and university hub, and proximity to the Arctic Circle.
 E160272 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: Luleå | Statement: [Kemi, twinTown, Luleå]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Luleå
Context triple: [Kemi, twinTown, Luleå]
  • A. Trollhättan
    Trollhättan is a city in western Sweden known for its historic role in the automotive industry and as the longtime home of Saab Automobile’s main production facilities.
  • B. Östersund
    Östersund is a city in central Sweden known for its strong winter sports tradition and repeated bids to host the Winter Olympics.
  • C. Strömstad
    Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
  • D. Linköping
    Linköping is a major city in southern Sweden known for its university, high-tech industry, and historic cathedral.
  • E. Jönköping
    Jönköping is a city in southern Sweden, located at the southern end of Lake Vättern and known as a regional commercial and logistical 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: Luleå
Triple: [Kemi, twinTown, Luleå]
Generated description
Luleå is a coastal city in northern Sweden known for its major port, technology and university hub, and proximity to the Arctic Circle.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Luleå
Target entity description: Luleå is a coastal city in northern Sweden known for its major port, technology and university hub, and proximity to the Arctic Circle.
  • A. Trollhättan
    Trollhättan is a city in western Sweden known for its historic role in the automotive industry and as the longtime home of Saab Automobile’s main production facilities.
  • B. Östersund
    Östersund is a city in central Sweden known for its strong winter sports tradition and repeated bids to host the Winter Olympics.
  • C. Strömstad
    Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
  • D. Linköping
    Linköping is a major city in southern Sweden known for its university, high-tech industry, and historic cathedral.
  • E. Jönköping
    Jönköping is a city in southern Sweden, located at the southern end of Lake Vättern and known as a regional commercial and logistical 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_69a493d848848190aed4011b34b2e8d3 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b82a1014819085bfc077e24c9742 completed March 1, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69acde0311d88190a3cd04c7e00253e2 completed March 8, 2026, 2:25 a.m.
NEDg Description generation batch_69acdfabfd3c8190960d8621b49284a8 completed March 8, 2026, 2:32 a.m.
NED2 Entity disambiguation (via description) batch_69ace0ea9d1c8190a73ed43b0a7bbd2f completed March 8, 2026, 2:37 a.m.
Created at: March 1, 2026, 7:41 p.m.