Triple

T14085282
Position Surface form Disambiguated ID Type / Status
Subject Daniel Sedin E338977 entity
Predicate placeOfBirth P1 FINISHED
Object Örnsköldsvik, Sweden E335730 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: Örnsköldsvik, Sweden | Statement: [Daniel Sedin, placeOfBirth, Örnsköldsvik, Sweden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Örnsköldsvik, Sweden
Context triple: [Daniel Sedin, placeOfBirth, Örnsköldsvik, Sweden]
  • A. Örnsköldsvik chosen
    Örnsköldsvik is a coastal town in northern Sweden known for its strong ice hockey tradition and as the hometown of several prominent NHL players.
  • 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. Landskrona, Sweden
    Landskrona, Sweden is a coastal city in southern Sweden’s Skåne County, known for its historic fortress, harbor, and local football culture.
  • 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. Helsingborg, Sweden
    Helsingborg, Sweden is a coastal city in southern Sweden known for its historic architecture, strategic location on the Öresund Strait, and role as a regional commercial and cultural 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_69d81c687b0c819087fd9ed4198403f8 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5edff1b881909ea56dc2429ef2dd completed April 14, 2026, 3:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd1930da6481908d17adc6f7bbedd4 completed May 7, 2026, 10:58 p.m.
Created at: April 9, 2026, 10:21 p.m.