Triple

T15448449
Position Surface form Disambiguated ID Type / Status
Subject Örebro E370085 entity
Predicate isOnRiver P165 FINISHED
Object Svartån E443510 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: Svartån | Statement: [Örebro, isOnRiver, Svartån]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Svartån
Context triple: [Örebro, isOnRiver, Svartån]
  • A. Svartån chosen
    Svartån is a river in central Sweden that flows through Örebro County, including the city of Örebro, before eventually joining larger water systems leading toward Lake Mälaren.
  • B. Bällstaån
    Bällstaån is a small river in the Stockholm area of Sweden that flows through several suburbs before emptying into Bällstaviken.
  • C. Storsjön
    Storsjön is a large lake in central Sweden, famed for its scenic surroundings and the local legend of the lake monster Storsjöodjuret.
  • D. Munksjön
    Munksjön is a small urban lake situated in central Jönköping in southern Sweden, known for its promenades, recreational areas, and proximity to the city’s downtown.
  • E. Järla Sjö
    Järla Sjö is a lake and residential area in the eastern suburbs of Stockholm, Sweden, known for its scenic waterfront setting within Nacka.
  • 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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ef9334c81908541e231b43eb012 completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4549074481908c12045632f11941 completed May 9, 2026, 2:31 p.m.
Created at: April 10, 2026, 3:21 a.m.