Triple

T7783173
Position Surface form Disambiguated ID Type / Status
Subject canton of Fribourg E187173 entity
Predicate containsTown P847 FINISHED
Object Romont E44938 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: Romont | Statement: [canton of Fribourg, containsTown, Romont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Romont
Context triple: [canton of Fribourg, containsTown, Romont]
  • A. Lausanne
    Lausanne is a major Swiss city on the shores of Lake Geneva, known for hosting the International Olympic Committee and its vibrant cultural and academic institutions.
  • B. Neuchâtel
    Neuchâtel is a French-speaking canton in western Switzerland known for its lakeside capital, watchmaking industry, and historic architecture.
  • C. Nyon
    Nyon is a Swiss town on the shores of Lake Geneva that serves as the administrative home of several major sports organizations, including UEFA.
  • D. Stettlen
    Stettlen is a municipality in the canton of Bern in Switzerland, situated just east of the city of Bern and functioning largely as a residential and commuter community.
  • E. Fribourg chosen
    Fribourg is a bilingual Swiss canton in western Switzerland known for its medieval capital city and location at the cultural boundary between French- and German-speaking regions.
  • 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_69ca82af2d2c8190963861f5e0b8bf21 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cadf1f9c648190ac2b06d0d54035ea completed March 30, 2026, 8:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69cc55cd2fa88190955c3c1cebea0cca completed March 31, 2026, 11:16 p.m.
Created at: March 30, 2026, 4:22 p.m.