Triple

T8308333
Position Surface form Disambiguated ID Type / Status
Subject Vaasa E194520 entity
Predicate hasPortConnectionTo P40470 FINISHED
Object Umeå E232990 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: Umeå | Statement: [Vaasa, hasPortConnectionTo, Umeå]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Umeå
Context triple: [Vaasa, hasPortConnectionTo, Umeå]
  • A. Umeå chosen
    Umeå is a university city in northern Sweden known for its cultural scene, research institutions, and role as a regional economic hub.
  • B. Luleå
    Luleå is a coastal city in northern Sweden known for its major port, technology and university hub, and proximity to the Arctic Circle.
  • C. Skellefteå
    Skellefteå is a city in northern Sweden known for its growing high-tech and green industry sector, particularly in battery manufacturing, as well as its ice hockey tradition.
  • D. Sundsvall
    Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
  • E. Uppsala
    Uppsala is a historic Swedish city north of Stockholm, known for its prestigious university, medieval cathedral, and role as a cultural and ecclesiastical center.
  • 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_69ca82e613e88190bf8139669bbd0d53 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f2c06608190bd21633af07a530b completed March 31, 2026, 8 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce8877499081909d8e3762e9c1ed2f completed April 2, 2026, 3:17 p.m.
Created at: March 30, 2026, 5:54 p.m.