Triple

T3189669
Position Surface form Disambiguated ID Type / Status
Subject Svealand E66788 entity
Predicate contains P35 FINISHED
Object Falun
Falun is a historic Swedish city known for its former copper mine, a UNESCO World Heritage Site, and as the capital of Dalarna County in central Sweden.
 E336558 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: Falun | Statement: [Svealand, contains, Falun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Falun
Context triple: [Svealand, contains, Falun]
  • A. Flon
    Flon is a central urban district in Lausanne, Switzerland, known for its transformed industrial warehouses, nightlife, shopping, and cultural venues.
  • B. Flen
    Flen is a small Swedish town known as the administrative center of Flen Municipality in the province of Södermanland.
  • C. Enying
    Enying is a small town in central Hungary known for its agricultural surroundings and location within Fejér County.
  • D. FALA
    FALA is the ICAO airport code for Lanseria International Airport, a major privately owned international airport serving the Johannesburg region in South Africa.
  • E. Fagasa
    Fagasa is a coastal village on the island of Tutuila in American Samoa, known for its scenic bay and surrounding rainforest-covered hills.
  • 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: Falun
Triple: [Svealand, contains, Falun]
Generated description
Falun is a historic Swedish city known for its former copper mine, a UNESCO World Heritage Site, and as the capital of Dalarna County in central Sweden.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Falun
Target entity description: Falun is a historic Swedish city known for its former copper mine, a UNESCO World Heritage Site, and as the capital of Dalarna County in central Sweden.
  • A. Flon
    Flon is a central urban district in Lausanne, Switzerland, known for its transformed industrial warehouses, nightlife, shopping, and cultural venues.
  • B. Flen
    Flen is a small Swedish town known as the administrative center of Flen Municipality in the province of Södermanland.
  • C. Enying
    Enying is a small town in central Hungary known for its agricultural surroundings and location within Fejér County.
  • D. FALA
    FALA is the ICAO airport code for Lanseria International Airport, a major privately owned international airport serving the Johannesburg region in South Africa.
  • E. Fagasa
    Fagasa is a coastal village on the island of Tutuila in American Samoa, known for its scenic bay and surrounding rainforest-covered hills.
  • 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_69ad8587c1bc8190a2595f2c22ee1001 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada6e67e948190afbd9cc6a3ade415 completed March 8, 2026, 4:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b24b9a9bc88190b7090bda8fe6260c completed March 12, 2026, 5:14 a.m.
NEDg Description generation batch_69b24d677ca8819094cb03360ac885da completed March 12, 2026, 5:21 a.m.
NED2 Entity disambiguation (via description) batch_69b25178f3c08190be78bdbd0cdfc5f3 completed March 12, 2026, 5:39 a.m.
Created at: March 8, 2026, 3:07 p.m.