Triple

T15543285
Position Surface form Disambiguated ID Type / Status
Subject Comasco E370535 entity
Predicate closelyRelatedTo P37 FINISHED
Object Brianzöö E665466 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: Brianzöö | Statement: [Comasco, closelyRelatedTo, Brianzöö]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brianzöö
Context triple: [Comasco, closelyRelatedTo, Brianzöö]
  • A. Brianzoeu chosen
    Brianzoeu is a regional dialect of the Lombard language spoken in parts of northern Italy.
  • B. Balzar
    Balzar is a town and agricultural center in coastal Ecuador, known for its rice and banana production within Guayas Province.
  • C. Zwenkau
    Zwenkau is a small town in the Free State of Saxony in eastern Germany, situated near Leipzig and known for its proximity to former lignite mining areas now being transformed into lake landscapes.
  • D. Belp
    Belp is a municipality in the canton of Bern in Switzerland, situated near the city of Bern and known for hosting Bern Airport.
  • E. Bruson
    Bruson is a quieter, traditional Swiss alpine village and ski area in the Valais region, known for its tree-lined slopes and access to the larger 4 Vallées domain.
  • 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_69d85cc521a08190921fb50319dddc34 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04432c3808190bb5b653bf8de30c6 completed April 16, 2026, 2:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4558677881908704ac86c12e1fc4 completed May 9, 2026, 2:31 p.m.
Created at: April 10, 2026, 4:07 a.m.