Triple

T17868023
Position Surface form Disambiguated ID Type / Status
Subject Sempach E446756 entity
Predicate district P2709 FINISHED
Object Sursee NE NERFINISHED

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: Sursee | Statement: [Sempach, district, Sursee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sursee
Context triple: [Sempach, district, Sursee]
  • A. Sursee chosen
    Sursee is a historic Swiss town in the canton of Lucerne, known for its well-preserved medieval old town and scenic setting near Lake Sempach.
  • B. Disentis
    Disentis is a Swiss Alpine village in the canton of Graubünden known for its Benedictine monastery and access to extensive skiing and mountain sports.
  • C. Oetwil am See
    Oetwil am See is a municipality in the canton of Zurich, Switzerland, known for its scenic location near Lake Zurich and its residential, semi-rural character.
  • D. Selzach
    Selzach is a Swiss municipality located in the canton of Solothurn, known for its rural character and proximity to the Jura Mountains.
  • E. Neuenegg
    Neuenegg is a Swiss municipality in the canton of Bern, known for its rural character and location near the city of Bern.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f4c22c819093c2680434472894 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49aa0b69081909fba3b42d237b543 completed April 19, 2026, 9:04 a.m.
Created at: April 10, 2026, 10:17 a.m.