Triple

T3356686
Position Surface form Disambiguated ID Type / Status
Subject Lake Zurich E70620 entity
Predicate hasNameInGerman P22792 FINISHED
Object Zürichsee E70620 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: Zürichsee | Statement: [Lake Zurich, hasNameInGerman, Zürichsee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zürichsee
Context triple: [Lake Zurich, hasNameInGerman, Zürichsee]
  • A. Lake Zurich chosen
    Lake Zurich is a picturesque glacial lake in Switzerland, bordered by the city of Zurich and known for its recreational activities, scenic promenades, and surrounding alpine landscapes.
  • B. 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.
  • C. 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.
  • D. 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.
  • 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 (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_69ad85a660c48190998489309a3b4869 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb242d4988190bbac993df587936d completed March 8, 2026, 5:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4e4d1c7188190b0f98fdc51e6684a completed March 14, 2026, 4:32 a.m.
Created at: March 8, 2026, 3:13 p.m.