Triple

T3189667
Position Surface form Disambiguated ID Type / Status
Subject Svealand E66788 entity
Predicate contains P35 FINISHED
Object Karlstad
Karlstad is a city in central Sweden known as the capital of Värmland County, situated on the northern shore of Lake Vänern.
 E370713 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: Karlstad | Statement: [Svealand, contains, Karlstad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Karlstad
Context triple: [Svealand, contains, Karlstad]
  • A. Sundsvall
    Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
  • B. Skövde
    Skövde is a town in south-central Sweden that serves as a major military hub and training center for the Swedish Army.
  • C. Eskilstuna
    Eskilstuna is an industrial city in central Sweden known historically for its metalworking and engineering industries.
  • D. Örebro
    Örebro is a historic city in central Sweden known for its medieval castle, university, and role as a regional economic and cultural hub.
  • E. Norrköping
    Norrköping is a historic industrial city in eastern Sweden known for its preserved textile mills, waterways, and cultural institutions.
  • 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: Karlstad
Triple: [Svealand, contains, Karlstad]
Generated description
Karlstad is a city in central Sweden known as the capital of Värmland County, situated on the northern shore of Lake Vänern.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Karlstad
Target entity description: Karlstad is a city in central Sweden known as the capital of Värmland County, situated on the northern shore of Lake Vänern.
  • A. Sundsvall
    Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
  • B. Skövde
    Skövde is a town in south-central Sweden that serves as a major military hub and training center for the Swedish Army.
  • C. Eskilstuna
    Eskilstuna is an industrial city in central Sweden known historically for its metalworking and engineering industries.
  • D. Örebro
    Örebro is a historic city in central Sweden known for its medieval castle, university, and role as a regional economic and cultural hub.
  • E. Norrköping
    Norrköping is a historic industrial city in eastern Sweden known for its preserved textile mills, waterways, and cultural institutions.
  • 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_69b402bcf7ec8190a7f0b7c0cc45e2f8 completed March 13, 2026, 12:27 p.m.
NEDg Description generation batch_69b403c9f6788190be21ee4c849fba60 completed March 13, 2026, 12:32 p.m.
NED2 Entity disambiguation (via description) batch_69b4086ab034819086c5fa7d4b172d75 completed March 13, 2026, 12:51 p.m.
Created at: March 8, 2026, 3:07 p.m.