Triple

T3707811
Position Surface form Disambiguated ID Type / Status
Subject Sils Maria E80934 entity
Predicate hasAttraction P105 FINISHED
Object Lake Sils E382884 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 Sils | Statement: [Sils Maria, hasAttraction, Lake Sils]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Sils
Context triple: [Sils Maria, hasAttraction, Lake Sils]
  • A. Lake Sils chosen
    Lake Sils is a scenic alpine lake in the Upper Engadine valley of the Swiss canton of Graubünden, renowned for its clear waters and surrounding mountain landscapes.
  • B. Lake Jacomo
    Lake Jacomo is a large recreational reservoir in Jackson County, Missouri, popular for boating, fishing, and outdoor activities within the Fleming Park area.
  • 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 Baldegg
    Lake Baldegg is a small glacial lake in central Switzerland known for its scenic surroundings and role in regional recreation and nature conservation.
  • E. 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.
  • 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_69ad8b1793888190a5f70e4b21dc05a1 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adc580b08481908391283778d5ce14 completed March 8, 2026, 6:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4db06e8e481908d1f026ce647a6a5 completed March 14, 2026, 3:50 a.m.
Created at: March 8, 2026, 3:33 p.m.