Triple

T15040414
Position Surface form Disambiguated ID Type / Status
Subject Söderort E378584 entity
Predicate hasPart P35 FINISHED
Object Hägersten
Hägersten is a residential district in southern Stockholm, Sweden, known for its mix of apartment blocks, green areas, and proximity to the city center.
E1141439 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: Hägersten | Statement: [Söderort, hasPart, Hägersten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hägersten
Context triple: [Söderort, hasPart, Hägersten]
  • A. Strömholm
    Strömholm is a Swedish surname most notably associated with Stig Strömholm, a prominent jurist and academic.
  • B. Lindhagen
    Lindhagen is a Swedish surname most notably associated with the politician and social reformer Carl Lindhagen.
  • C. Häger
    Häger is a surname and place name of Germanic origin that appears as a variant spelling of Hager.
  • D. Häggvik
    Häggvik is a residential and commercial district in Sollentuna, part of the northern suburbs of Stockholm, Sweden.
  • E. Eidskog
    Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
  • 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: Hägersten
Triple: [Söderort, hasPart, Hägersten]
Generated description
Hägersten is a residential district in southern Stockholm, Sweden, known for its mix of apartment blocks, green areas, and proximity to the city center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hägersten
Target entity description: Hägersten is a residential district in southern Stockholm, Sweden, known for its mix of apartment blocks, green areas, and proximity to the city center.
  • A. Strömholm
    Strömholm is a Swedish surname most notably associated with Stig Strömholm, a prominent jurist and academic.
  • B. Lindhagen
    Lindhagen is a Swedish surname most notably associated with the politician and social reformer Carl Lindhagen.
  • C. Häger
    Häger is a surname and place name of Germanic origin that appears as a variant spelling of Hager.
  • D. Häggvik
    Häggvik is a residential and commercial district in Sollentuna, part of the northern suburbs of Stockholm, Sweden.
  • E. Eidskog
    Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
  • 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_69d85cd46b2c819090d054c27787f677 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded82e79a481908ddb9609af8c4407 completed April 15, 2026, 12:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69fec87725348190a0da7555b62adbdc completed May 9, 2026, 5:39 a.m.
NEDg Description generation batch_69fec9d32f388190aef036dde9cdda42 completed May 9, 2026, 5:44 a.m.
NED2 Entity disambiguation (via description) batch_69feca4a9db08190a083b5f0d9ec091b completed May 9, 2026, 5:46 a.m.
Created at: April 10, 2026, 3 a.m.