Triple

T13418111
Position Surface form Disambiguated ID Type / Status
Subject European route E10 E313266 entity
Predicate terminusB P388 FINISHED
Object Luleå, Sweden E160272 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: Luleå, Sweden | Statement: [European route E10, terminusB, Luleå, Sweden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luleå, Sweden
Context triple: [European route E10, terminusB, Luleå, Sweden]
  • A. Luleå chosen
    Luleå is a coastal city in northern Sweden known for its major port, technology and university hub, and proximity to the Arctic Circle.
  • B. Södertälje, Sweden
    Södertälje, Sweden is an industrial city southwest of Stockholm known for its major manufacturing plants, particularly in the automotive and heavy vehicle sectors.
  • 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. Karlskoga, Sweden
    Karlskoga, Sweden is an industrial town in central Sweden best known for its historic arms manufacturer Bofors and its association with Alfred Nobel.
  • E. Älmhult, Sweden
    Älmhult, Sweden is a small town in southern Sweden best known as the birthplace and original home of the global furniture company IKEA.
  • 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_69d806ad0c44819088833ae1ec9e9690 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaeb8416c8190a00dde0917c26f51 completed April 12, 2026, 2:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69f73082a2548190aefc0f202b84165c completed May 3, 2026, 11:24 a.m.
Created at: April 9, 2026, 9:39 p.m.