Triple

T15040389
Position Surface form Disambiguated ID Type / Status
Subject Söderort E378584 entity
Predicate hasPart P35 FINISHED
Object Farsta E578135 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: Farsta | Statement: [Söderort, hasPart, Farsta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Farsta
Context triple: [Söderort, hasPart, Farsta]
  • A. Farsta chosen
    Farsta is a suburban district in southern Stockholm, Sweden, known for its residential areas, shopping center, and metro connections to the city center.
  • B. Fámjin
    Fámjin is a small coastal village on the west coast of Suðuroy in the Faroe Islands, known for its dramatic sea cliffs and historic church that houses the first Faroese flag.
  • C. Evenstad
    Evenstad is a small Norwegian locality known for hosting a campus of the Inland Norway University of Applied Sciences, particularly focused on environmental and wildlife-related studies.
  • D. Märsta
    Märsta is a town in Stockholm County, Sweden, known as a residential and transport hub near Stockholm Arlanda Airport.
  • E. Faist
    Faist is a surname most notably associated with American actor Mike Faist, known for his work on stage and in film.
  • 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_69d85cd46b2c819090d054c27787f677 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded82e79a481908ddb9609af8c4407 completed April 15, 2026, 12:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69fea5b75c04819085996a7f88ab6c38 completed May 9, 2026, 3:10 a.m.
Created at: April 10, 2026, 3 a.m.