Triple

T4340757
Position Surface form Disambiguated ID Type / Status
Subject Norrmalm E97572 entity
Predicate hasStreet P959 FINISHED
Object Vasagatan
Vasagatan is a major central street in Stockholm, Sweden, known for its busy traffic, shops, and proximity to Stockholm Central Station.
 E432135 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: Vasagatan | Statement: [Norrmalm, hasStreet, Vasagatan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vasagatan
Context triple: [Norrmalm, hasStreet, Vasagatan]
  • A. Stora Värtan
    Stora Värtan is a bay of the Baltic Sea in the Stockholm archipelago, known for its coastal residential areas, marinas, and recreational boating.
  • B. Dalälven
    Dalälven is a major river in central Sweden known for its extensive watershed, hydroelectric power stations, and rich natural and recreational areas.
  • C. Ångerman River
    The Ångerman River is a major river in northern Sweden known for its long course through forested landscapes before emptying into the Gulf of Bothnia.
  • D. Veavågen
    Veavågen is a coastal village in Karmøy municipality in Rogaland county, Norway, known for its fishing industry and maritime character.
  • E. Avre
    The Avre is a river in northern France that serves as a tributary of the Eure, flowing through the Normandy and Centre-Val de Loire regions.
  • 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: Vasagatan
Triple: [Norrmalm, hasStreet, Vasagatan]
Generated description
Vasagatan is a major central street in Stockholm, Sweden, known for its busy traffic, shops, and proximity to Stockholm Central Station.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vasagatan
Target entity description: Vasagatan is a major central street in Stockholm, Sweden, known for its busy traffic, shops, and proximity to Stockholm Central Station.
  • A. Stora Värtan
    Stora Värtan is a bay of the Baltic Sea in the Stockholm archipelago, known for its coastal residential areas, marinas, and recreational boating.
  • B. Dalälven
    Dalälven is a major river in central Sweden known for its extensive watershed, hydroelectric power stations, and rich natural and recreational areas.
  • C. Ångerman River
    The Ångerman River is a major river in northern Sweden known for its long course through forested landscapes before emptying into the Gulf of Bothnia.
  • D. Veavågen
    Veavågen is a coastal village in Karmøy municipality in Rogaland county, Norway, known for its fishing industry and maritime character.
  • E. Avre
    The Avre is a river in northern France that serves as a tributary of the Eure, flowing through the Normandy and Centre-Val de Loire regions.
  • 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_69b3454662a481908fbcd0bbfaa3a0a4 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35170a6648190a15ffb21640ee478 completed March 12, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d0b301188190af8514a675aebb5f completed March 14, 2026, 9:18 p.m.
NEDg Description generation batch_69b5d137271c8190a2d66fb47eb10d93 completed March 14, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_69b5d4e5e24c8190980bc545ca0d339d completed March 14, 2026, 9:36 p.m.
Created at: March 12, 2026, 11:14 p.m.