Triple

T12182791
Position Surface form Disambiguated ID Type / Status
Subject Wallander E290260 entity
Predicate setting P1957 FINISHED
Object Ystad E652448 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: Ystad | Statement: [Wallander, setting, Ystad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ystad
Context triple: [Wallander, setting, Ystad]
  • A. Ystad chosen
    Ystad is a historic coastal town in southern Sweden known for its medieval architecture and as the setting of Henning Mankell’s Kurt Wallander crime novels.
  • B. Strömstad
    Strömstad is a coastal town and municipality in western Sweden, near the Norwegian border, known for its archipelago, tourism, and ferry connections.
  • C. Kristianstad
    Kristianstad is a historic city in southern Sweden known for its well-preserved Renaissance architecture and proximity to the wetlands of the Kristianstad Vattenrike Biosphere Reserve.
  • D. Halmstad
    Halmstad is a coastal city in southwestern Sweden known for its historic town center, harbor, and role as a strategic site in Scandinavian conflicts.
  • E. Halmstad
    Halmstad is a village in Moss municipality in Viken county, southeastern Norway.
  • 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_69d6ab64de5881908d56eb7a75c6cc69 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d915fd8dac8190928059ad2b6bbbf3 completed April 10, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69f71f05b3e08190be0d4e0ad2bfb2d1 completed May 3, 2026, 10:10 a.m.
Created at: April 8, 2026, 9:50 p.m.