Triple

T11216393
Position Surface form Disambiguated ID Type / Status
Subject Swedish west coast E265448 entity
Predicate hasTown P847 FINISHED
Object Halmstad E218044 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: Halmstad | Statement: [Swedish west coast, hasTown, Halmstad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Halmstad
Context triple: [Swedish west coast, hasTown, Halmstad]
  • A. Halmstad chosen
    Halmstad is a coastal city in southwestern Sweden known for its historic town center, harbor, and role as a strategic site in Scandinavian conflicts.
  • B. Halmstad
    Halmstad is a village in Moss municipality in Viken county, southeastern Norway.
  • 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. Sundsvall
    Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
  • E. Ystad
    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.
  • 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_69d6aac59460819089b9848b27f57848 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8e8eef48190932a85784ce15c86 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c0ce0a508190a2f44cbe812b5f17 completed May 3, 2026, 3:28 a.m.
Created at: April 8, 2026, 9:30 p.m.