Triple

T17482046
Position Surface form Disambiguated ID Type / Status
Subject Wassen E425683 entity
Predicate locatedSouthOf P9676 FINISHED
Object Lake Lucerne 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: Lake Lucerne | Statement: [Wassen, locatedSouthOf, Lake Lucerne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Lucerne
Context triple: [Wassen, locatedSouthOf, Lake Lucerne]
  • A. Lake Lucerne
    Lake Lucerne is a residential community in Miami Gardens, Florida, known for its suburban character within the Miami metropolitan area.
  • B. Lake Lucerne chosen
    Lake Lucerne is a picturesque, fjord-like lake in central Switzerland, renowned for its dramatic mountain scenery, historic sites, and role as a major tourist destination.
  • C. Lake Thun
    Lake Thun is a large alpine lake in the Bernese Oberland region of Switzerland, renowned for its scenic mountain backdrop, historic lakeside towns, and popular boating and water sports.
  • D. Lake of Biel
    Lake of Biel is a scenic lake in western Switzerland’s Seeland region, known for its vineyards, islands, and role in the Jura water correction system.
  • E. Lake Brienz
    Lake Brienz is a deep, turquoise-colored alpine lake in central Switzerland, renowned for its dramatic mountain scenery and crystal-clear waters.
  • 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_69d889dccf7481909264a1844a2e9100 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e451c0db14819098922453131fb40a completed April 19, 2026, 3:53 a.m.
Created at: April 10, 2026, 5:48 a.m.