Triple

T3145535
Position Surface form Disambiguated ID Type / Status
Subject Västra Götaland County E65754 entity
Predicate contains P35 FINISHED
Object Lidköping
Lidköping is a Swedish town on the southern shore of Lake Vänern known for its historic center, ceramics industry, and role as a local commercial hub.
 E360442 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: Lidköping | Statement: [Västra Götaland County, contains, Lidköping]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lidköping
Context triple: [Västra Götaland County, contains, Lidköping]
  • A. Norrköping
    Norrköping is a historic industrial city in eastern Sweden known for its preserved textile mills, waterways, and cultural institutions.
  • B. Nyköping
    Nyköping is a historic coastal town in southeastern Sweden known for its medieval castle, harbor, and role as a regional administrative and cultural center.
  • C. Sundsvall
    Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
  • 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: Lidköping
Triple: [Västra Götaland County, contains, Lidköping]
Generated description
Lidköping is a Swedish town on the southern shore of Lake Vänern known for its historic center, ceramics industry, and role as a local commercial hub.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lidköping
Target entity description: Lidköping is a Swedish town on the southern shore of Lake Vänern known for its historic center, ceramics industry, and role as a local commercial hub.
  • A. Norrköping
    Norrköping is a historic industrial city in eastern Sweden known for its preserved textile mills, waterways, and cultural institutions.
  • B. Nyköping
    Nyköping is a historic coastal town in southeastern Sweden known for its medieval castle, harbor, and role as a regional administrative and cultural center.
  • C. Sundsvall
    Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
  • 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_69ad8582f564819088c27e1f96153938 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada59797788190a8d71262888c5df0 completed March 8, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69b367e5581081908c44bc8d9492c936 completed March 13, 2026, 1:27 a.m.
NEDg Description generation batch_69b368d21f7c819092660301b7d840db completed March 13, 2026, 1:30 a.m.
NED2 Entity disambiguation (via description) batch_69b3694e92b8819082d54a56d901e9f8 completed March 13, 2026, 1:33 a.m.
Created at: March 8, 2026, 3:05 p.m.