Triple

T20499420
Position Surface form Disambiguated ID Type / Status
Subject Thun–Spiez railway line E503260 entity
Predicate passesAlong P11198 FINISHED
Object Lake Thun 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 Thun | Statement: [Thun–Spiez railway line, passesAlong, Lake Thun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Thun
Context triple: [Thun–Spiez railway line, passesAlong, Lake Thun]
  • A. Lake Thun chosen
    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.
  • B. 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.
  • C. Lake Brienz
    Lake Brienz is a deep, turquoise-colored alpine lake in central Switzerland, renowned for its dramatic mountain scenery and crystal-clear waters.
  • D. Oeschinen Lake
    Oeschinen Lake is a scenic alpine lake in the Bernese Oberland region of Switzerland, renowned for its turquoise waters, dramatic mountain backdrop, and outdoor recreation opportunities.
  • E. Walensee
    Walensee is a picturesque alpine lake in eastern Switzerland, known for its steep surrounding mountains and clear turquoise 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_69e0b4b1e52c8190894281cf7e3283ab completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e69cc10cd08190915b6c29c6473f77 completed April 20, 2026, 9:38 p.m.
Created at: April 16, 2026, 11:35 a.m.