Triple

T15719208
Position Surface form Disambiguated ID Type / Status
Subject Sihlsee dam E381044 entity
Predicate reservoirName P13043 FINISHED
Object Lake Sihl E1173051 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 Sihl | Statement: [Sihlsee dam, reservoirName, Lake Sihl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Sihl
Context triple: [Sihlsee dam, reservoirName, Lake Sihl]
  • A. Lake Sihl chosen
    Lake Sihl is a large reservoir in the Swiss canton of Schwyz, primarily used for hydroelectric power generation and flood protection for the city of Zurich.
  • 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 Sempach
    Lake Sempach is a small lake in central Switzerland, known for its scenic surroundings, birdlife, and recreational activities such as swimming and boating.
  • D. Immensee
    Immensee is a picturesque lakeside village in the Swiss canton of Schwyz, known for its scenic setting on the shores of Lake Zug.
  • 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_69d86d9bf930819082b30cf6d169297c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f932a248190b65ecfb2bc56e715 completed April 16, 2026, 2:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff82f464008190ae0e79f50b9b3eb3 completed May 9, 2026, 6:54 p.m.
Created at: April 10, 2026, 4:45 a.m.