Triple

T9610385
Position Surface form Disambiguated ID Type / Status
Subject Sauerland E232082 entity
Predicate contains P35 FINISHED
Object Sorpesee E228424 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: Sorpesee | Statement: [Sauerland, contains, Sorpesee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sorpesee
Context triple: [Sauerland, contains, Sorpesee]
  • A. Sorpesee chosen
    Sorpesee is a popular artificial lake in the Sauerland region of Germany, known for recreation, water sports, and scenic surroundings.
  • B. La Rippe
    La Rippe is a small Swiss municipality in the canton of Vaud, located near the Jura Mountains and close to the French border.
  • C. Beloeil
    Beloeil is a suburban city in southwestern Quebec, Canada, located along the Richelieu River opposite Mont-Saint-Hilaire and forming part of the greater Montreal area.
  • D. Unterseen
    Unterseen is a historic Swiss town in the Bernese Oberland, situated near Interlaken at the confluence of the Aare and Lombach rivers with views of the surrounding Alps.
  • E. Garrelsweer
    Garrelsweer is a small village in the province of Groningen in the Netherlands, situated within the municipality of Eemsdelta.
  • 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_69ca8485a90c819094fe40b42fde9d70 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9a85d4c881909ccab2e972d97e68 completed April 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69d179491ecc8190a72be68cc5f572b2 completed April 4, 2026, 8:49 p.m.
Created at: March 30, 2026, 8:08 p.m.