Triple

T21239460
Position Surface form Disambiguated ID Type / Status
Subject Djursholms Ösby station E523431 entity
Predicate connectsTo P845 FINISHED
Object Åkersberga 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: Åkersberga | Statement: [Djursholms Ösby station, connectsTo, Åkersberga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Åkersberga
Context triple: [Djursholms Ösby station, connectsTo, Åkersberga]
  • A. Åkersberga chosen
    Åkersberga is a suburban town in eastern Sweden that serves as the main population and service center of Österåker Municipality, northeast of Stockholm.
  • B. Åberg
    Åberg is a Swedish surname borne by various notable individuals across fields such as sports, music, and the arts.
  • C. Häggenås
    Häggenås is a small locality in Jämtland County, northern Sweden, situated within Östersund Municipality.
  • D. Fagersta
    Fagersta is an industrial town in central Sweden known for its steel production and manufacturing heritage.
  • E. Kyrkslätt
    Kyrkslätt is the Swedish name for Kirkkonummi, a coastal municipality in southern Finland located just west of Helsinki.
  • 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_69e0b513b89c81908b27147e91368db2 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e73522acdc8190b3e155026a0445cd completed April 21, 2026, 8:28 a.m.
Created at: April 16, 2026, 3:46 p.m.