Triple

T15815445
Position Surface form Disambiguated ID Type / Status
Subject Sihlsee E383463 entity
Predicate createdBy P806 FINISHED
Object Sihlsee dam E381044 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: Sihlsee dam | Statement: [Sihlsee, createdBy, Sihlsee dam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sihlsee dam
Context triple: [Sihlsee, createdBy, Sihlsee dam]
  • A. Sihlsee dam chosen
    The Sihlsee dam is a Swiss hydroelectric dam that creates Lake Sihl, a reservoir used for power generation and flood control near Zurich.
  • B. Sihlsee
    Sihlsee is an artificial lake in the Swiss canton of Schwyz, created by damming the Sihl River and used primarily for hydroelectric power generation and recreation.
  • C. Pilsensee
    Pilsensee is a small scenic lake in Bavaria, Germany, known for its clear waters, recreational opportunities, and location within the popular Five Lakes Region near Munich.
  • D. Lake Sihl
    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.
  • E. Schlosssee
    Schlosssee is a scenic lake in the spa town of Bad Waldsee in southern Germany, known for recreation and its picturesque natural setting.
  • 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_69d86da2858c819090cc8481e7207b6e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0c4a219508190b8588120ec415ac7 completed April 16, 2026, 11:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffb5997a988190b7965e42d283459a completed May 9, 2026, 10:30 p.m.
Created at: April 10, 2026, 4:49 a.m.