Triple

T7005972
Position Surface form Disambiguated ID Type / Status
Subject Enebyberg E162456 entity
Predicate nearbyLocality P4647 FINISHED
Object Stocksund E142116 NE FINISHED

How this triple was built (2 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: Stocksund | Statement: [Enebyberg, nearbyLocality, Stocksund]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stocksund
Context triple: [Enebyberg, nearbyLocality, Stocksund]
  • A. Stocksund chosen
    Stocksund is an affluent residential suburb in the Stockholm urban area, known for its villas, waterfront location, and proximity to central Stockholm.
  • B. Stegesund
    Stegesund is a small island in the Stockholm archipelago of Sweden, known for its scenic coastal setting and proximity to the town of Vaxholm.
  • C. Børselv
    Børselv is a small coastal village in northern Norway known for its scenic Arctic surroundings and traditional Sámi cultural heritage.
  • D. Hokksund
    Hokksund is a small town in southeastern Norway known as the administrative center of Øvre Eiker municipality in Viken county.
  • E. Stabekk
    Stabekk is a suburban area in Bærum, Norway, known for its residential neighborhoods, proximity to Oslo, and good transport connections.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c6885928148190ae31909fbb5e9849 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dc34b5a88190a793e07dd4d0018b completed March 27, 2026, 7:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76a3f5a088190bd0fa2080a8fa648 completed March 28, 2026, 5:42 a.m.
Created at: March 27, 2026, 2:33 p.m.