Triple

T2898119
Position Surface form Disambiguated ID Type / Status
Subject Aare E62590 entity
Predicate flowsThrough P225 FINISHED
Object Thun E113677 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: Thun | Statement: [Aare, flowsThrough, Thun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thun
Context triple: [Aare, flowsThrough, Thun]
  • A. Thun chosen
    Thun is a historic Swiss town in the canton of Bern, known for its medieval old town, lakeside setting on Lake Thun, and views of the surrounding Alps.
  • B. Oberegg
    Oberegg is a Swiss municipality in the canton of Appenzell Innerrhoden, known for its rural landscape and location in the Appenzell region.
  • C. Saas-Fee
    Saas-Fee is a high-altitude Swiss alpine village and ski resort in the Valais Alps, known for its car-free center, extensive glacier skiing, and dramatic mountain scenery.
  • D. Meyrin
    Meyrin is a municipality in the canton of Geneva, Switzerland, best known for hosting major CERN facilities including the Super Proton Synchrotron.
  • E. Aarberg
    Aarberg is a small historic town in the canton of Bern in Switzerland, known for its medieval center and distinctive wooden bridge over the Aare River.
  • 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_69ab4c3e070c8190b78d3d2c005876dd completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abe08fe3248190a6bb7de2a2c317b1 completed March 7, 2026, 8:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69b03188d84081909e23b46c2f75250b completed March 10, 2026, 2:58 p.m.
Created at: March 6, 2026, 10:10 p.m.