Triple

T1245495
Position Surface form Disambiguated ID Type / Status
Subject Danderyd Municipality E26753 entity
Predicate hasCoastlineOn P212 FINISHED
Object Edsviken
Edsviken is a narrow bay of the Baltic Sea in the Stockholm area, known for its residential waterfronts, marinas, and recreational natural surroundings.
E164484 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: Edsviken | Statement: [Danderyd Municipality, hasCoastlineOn, Edsviken]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Edsviken
Context triple: [Danderyd Municipality, hasCoastlineOn, Edsviken]
  • A. Enebyberg
    Enebyberg is a residential suburban area in the northern part of the Stockholm urban region in Sweden.
  • B. Djursholm
    Djursholm is an affluent suburban district of Stockholm, Sweden, known for its villas, garden-city planning, and status as one of the country’s wealthiest residential areas.
  • C. Skarpäng
    Skarpäng is a residential urban area within Täby Municipality in Stockholm County, Sweden.
  • D. Älvdalen
    Älvdalen is a small municipality in central Sweden known for its forested landscapes, traditional culture, and preservation of the unique Elfdalian language.
  • E. Västerhaninge
    Västerhaninge is a suburban locality in Stockholm County, Sweden, known as a residential community within the Haninge area.
  • 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: Edsviken
Triple: [Danderyd Municipality, hasCoastlineOn, Edsviken]
Generated description
Edsviken is a narrow bay of the Baltic Sea in the Stockholm area, known for its residential waterfronts, marinas, and recreational natural surroundings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Edsviken
Target entity description: Edsviken is a narrow bay of the Baltic Sea in the Stockholm area, known for its residential waterfronts, marinas, and recreational natural surroundings.
  • A. Enebyberg
    Enebyberg is a residential suburban area in the northern part of the Stockholm urban region in Sweden.
  • B. Djursholm
    Djursholm is an affluent suburban district of Stockholm, Sweden, known for its villas, garden-city planning, and status as one of the country’s wealthiest residential areas.
  • C. Skarpäng
    Skarpäng is a residential urban area within Täby Municipality in Stockholm County, Sweden.
  • D. Älvdalen
    Älvdalen is a small municipality in central Sweden known for its forested landscapes, traditional culture, and preservation of the unique Elfdalian language.
  • E. Västerhaninge
    Västerhaninge is a suburban locality in Stockholm County, Sweden, known as a residential community within the Haninge area.
  • 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_69a4948689d08190b3a4a3f388c02148 completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4bf6498948190b30b09d845d67ac4 completed March 1, 2026, 10:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad014954b08190a787d7e03e503d8d completed March 8, 2026, 4:55 a.m.
NEDg Description generation batch_69ad039c5d788190aa10636e2827b489 completed March 8, 2026, 5:05 a.m.
NED2 Entity disambiguation (via description) batch_69ad03fa7b0c8190906ed79f24723216 completed March 8, 2026, 5:07 a.m.
Created at: March 1, 2026, 7:47 p.m.