Triple

T5431112
Position Surface form Disambiguated ID Type / Status
Subject Södertörn University E121491 entity
Predicate campus P269 FINISHED
Object Flemingsberg E137379 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: Flemingsberg | Statement: [Södertörn University, campus, Flemingsberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Flemingsberg
Context triple: [Södertörn University, campus, Flemingsberg]
  • A. Flemingsberg chosen
    Flemingsberg is a district in the southern Stockholm urban area known for its major university campus, hospital, and commuter rail hub.
  • B. Gustavsberg
    Gustavsberg is a locality in Sweden best known for its historic porcelain factory and role as a suburban community in the Stockholm archipelago.
  • C. Skarpäng
    Skarpäng is a residential urban area within Täby Municipality in Stockholm County, Sweden.
  • D. Siljan
    Siljan is a lake in Telemark, Norway, known for its scenic surroundings and proximity to the town of Skien.
  • E. Eidskog
    Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
  • 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_69bd463c65f0819082ee6483ab4b466a completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd883f982c8190bdf277e1ba85ff7b completed March 20, 2026, 5:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf3ac985e48190ba9610e0563c73ab completed March 22, 2026, 12:41 a.m.
Created at: March 20, 2026, 2:06 p.m.