Triple

T10870524
Position Surface form Disambiguated ID Type / Status
Subject Uri E256636 entity
Predicate hasLake P1025 FINISHED
Object Lake Lucerne E162352 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: Lake Lucerne | Statement: [Uri, hasLake, Lake Lucerne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Lucerne
Context triple: [Uri, hasLake, Lake Lucerne]
  • A. 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.
  • B. 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.
  • C. 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.
  • D. Lake Brienz
    Lake Brienz is a deep, turquoise-colored alpine lake in central Switzerland, renowned for its dramatic mountain scenery and crystal-clear waters.
  • E. Lake Sarnen
    Lake Sarnen is a scenic alpine lake in the canton of Obwalden in central Switzerland, known for its clear waters and surrounding mountain landscapes.
  • 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_69d6aa83d1448190a66d93c32394d21f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7518610e48190bee50db71ae0ca3e completed April 9, 2026, 7:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d6d70e90819093ced18f59785ab9 completed April 18, 2026, 12:56 a.m.
Created at: April 8, 2026, 9:20 p.m.