Triple

T14415550
Position Surface form Disambiguated ID Type / Status
Subject Pully E357440 entity
Predicate hasNeighboringMunicipality P224 FINISHED
Object Lutry E261420 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: Lutry | Statement: [Pully, hasNeighboringMunicipality, Lutry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lutry
Context triple: [Pully, hasNeighboringMunicipality, Lutry]
  • A. Lutry chosen
    Lutry is a picturesque Swiss village on the shores of Lake Geneva, known for its historic old town and its role as a gateway to the UNESCO-listed Lavaux terraced vineyards.
  • B. Lurtigen
    Lurtigen is a small former municipality in the canton of Fribourg in western Switzerland.
  • C. Prittitz
    Prittitz is a small municipality in the German state of Saxony-Anhalt that lies within the broader Leipzig metropolitan area.
  • D. Livarot
    Livarot is a small town in the Normandy region of northwestern France, historically known for its production of the pungent Livarot cheese.
  • E. Lanaken
    Lanaken is a municipality in the Belgian province of Limburg, known for its proximity to Maastricht and its mix of residential areas, industry, and natural landscapes.
  • 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_69d82793421c8190861eb0e673b085de completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de90cc99208190a2313b1acfb5d802 completed April 14, 2026, 7:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd552a75ec8190b966d509d315ca60 completed May 8, 2026, 3:14 a.m.
Created at: April 10, 2026, 1:17 a.m.