Triple

T11370989
Position Surface form Disambiguated ID Type / Status
Subject Garðabær E269339 entity
Predicate hasTwinTown P919 FINISHED
Object Eslöv
Eslöv is a small town in southern Sweden’s Skåne County, known as a local commercial and service center surrounded by agricultural countryside.
E925804 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: Eslöv | Statement: [Garðabær, hasTwinTown, Eslöv]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eslöv
Context triple: [Garðabær, hasTwinTown, Eslöv]
  • A. Svalöv
    Svalöv is a small locality and municipality in Skåne County in southern Sweden, known for its rural landscape and agricultural surroundings.
  • B. Oskarshamn
    Oskarshamn is a coastal town in southeastern Sweden known for its Baltic Sea harbor and proximity to the island of Gotland.
  • C. Hjulsta
    Hjulsta is a suburb in northwestern Stockholm, Sweden, known for being the terminus of one of the Stockholm metro lines.
  • D. Söderort
    Söderort is the southern suburban part of Stockholm, Sweden, consisting mainly of residential districts located south of the inner-city island of Södermalm.
  • E. Sandviken
    Sandviken is an industrial town in central Sweden, best known as the historic home of the steel company Sandvik.
  • 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: Eslöv
Triple: [Garðabær, hasTwinTown, Eslöv]
Generated description
Eslöv is a small town in southern Sweden’s Skåne County, known as a local commercial and service center surrounded by agricultural countryside.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Eslöv
Target entity description: Eslöv is a small town in southern Sweden’s Skåne County, known as a local commercial and service center surrounded by agricultural countryside.
  • A. Svalöv
    Svalöv is a small locality and municipality in Skåne County in southern Sweden, known for its rural landscape and agricultural surroundings.
  • B. Oskarshamn
    Oskarshamn is a coastal town in southeastern Sweden known for its Baltic Sea harbor and proximity to the island of Gotland.
  • C. Hjulsta
    Hjulsta is a suburb in northwestern Stockholm, Sweden, known for being the terminus of one of the Stockholm metro lines.
  • D. Söderort
    Söderort is the southern suburban part of Stockholm, Sweden, consisting mainly of residential districts located south of the inner-city island of Södermalm.
  • E. Sandviken
    Sandviken is an industrial town in central Sweden, best known as the historic home of the steel company Sandvik.
  • 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_69d6aacca1048190b39dbbc2174616fa completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea8b196881909af9b138661e816d completed April 9, 2026, 6:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5d32db0d081908f5a8f6ca1357997 completed April 20, 2026, 7:18 a.m.
NEDg Description generation batch_69e5d5cac9108190b7756329bfa320d3 completed April 20, 2026, 7:29 a.m.
NED2 Entity disambiguation (via description) batch_69e5d7f238cc8190a1c2dd26bdc5ff77 completed April 20, 2026, 7:38 a.m.
Created at: April 8, 2026, 9:33 p.m.