Triple

T4140403
Position Surface form Disambiguated ID Type / Status
Subject Henrik Lundqvist E89256 entity
Predicate placeOfBirth P1 FINISHED
Object Åre, Sweden E88146 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: Åre, Sweden | Statement: [Henrik Lundqvist, placeOfBirth, Åre, Sweden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Åre, Sweden
Context triple: [Henrik Lundqvist, placeOfBirth, Åre, Sweden]
  • A. Åre chosen
    Åre is a well-known ski resort village in northern Sweden, recognized for its alpine skiing and winter sports tourism.
  • B. 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.
  • C. 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.
  • D. Växjö, Sweden
    Växjö is a mid-sized city in southern Sweden known for its environmental sustainability initiatives, universities, and role as a regional cultural and economic center in Småland.
  • E. Hudiksvall
    Hudiksvall is a coastal town in east-central Sweden known for its historic wooden buildings and harbor on the Gulf of Bothnia.
  • 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_69aed95785788190ae75bcf0cd1cafdf completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0249dd988190bf6826a744e7771f completed March 9, 2026, 5:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69b576ccdf348190a80305485bee354e completed March 14, 2026, 2:55 p.m.
Created at: March 9, 2026, 3:43 p.m.