Triple

T21510103
Position Surface form Disambiguated ID Type / Status
Subject Vagnhärad E530693 entity
Predicate nearbyLocality P4647 FINISHED
Object Västerljung NE NERFINISHED

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: Västerljung | Statement: [Vagnhärad, nearbyLocality, Västerljung]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Västerljung
Context triple: [Vagnhärad, nearbyLocality, Västerljung]
  • A. Västerljung chosen
    Västerljung is a small locality in eastern Sweden situated within Trosa Municipality in Södermanland County.
  • B. Österskär
    Österskär is a coastal locality in Österåker Municipality, Sweden, known as a residential seaside area within the Stockholm archipelago.
  • C. Marstrandsön
    Marstrandsön is a Swedish island on the west coast known for the historic fortress town of Marstrand, sailing events, and scenic coastal landscapes.
  • D. Adelsö
    Adelsö is an island in Sweden’s Lake Mälaren known for its rich Viking Age history and archaeological sites.
  • E. Skarpö
    Skarpö is an island in the Stockholm archipelago of Sweden, situated within Vaxholm Municipality and known for its coastal scenery and residential character.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c45c81f08190a6b8bbb70a45aae7 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea84dfbc8190a23d9a7d6eb2c2b5 completed April 23, 2026, 9:46 a.m.
Created at: April 16, 2026, 6:25 p.m.