Triple

T11216392
Position Surface form Disambiguated ID Type / Status
Subject Swedish west coast E265448 entity
Predicate hasTown P847 FINISHED
Object Falkenberg E553784 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: Falkenberg | Statement: [Swedish west coast, hasTown, Falkenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Falkenberg
Context triple: [Swedish west coast, hasTown, Falkenberg]
  • A. Falkenberg chosen
    Falkenberg is a coastal town in southwestern Sweden known for its beaches, fishing heritage, and location along the River Ätran.
  • B. Falkenberg
    Falkenberg is a locality in the borough of Lichtenberg in Berlin, Germany, known for its more rural character on the city's northeastern edge.
  • C. Falköping
    Falköping is a small Swedish town known for its surrounding ancient burial mounds, rolling agricultural landscape, and location between the plateaus of Mösseberg and Ålleberg.
  • D. Fagersta
    Fagersta is an industrial town in central Sweden known for its steel production and manufacturing heritage.
  • E. Bengtsfors
    Bengtsfors is a small town in western Sweden known for its lakeside setting, forests, and role as a local administrative and service 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_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_69e58af8bc988190805168188ed0a6aa completed April 20, 2026, 2:10 a.m.
Created at: April 8, 2026, 9:30 p.m.