Triple

T19144957
Position Surface form Disambiguated ID Type / Status
Subject Municipality of Viedma E468654 entity
Predicate locatedIn P40 FINISHED
Object Viedma NE NERFINISHED

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: Viedma | Statement: [Municipality of Viedma, locatedIn, Viedma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viedma
Context triple: [Municipality of Viedma, locatedIn, Viedma]
  • A. Viedma chosen
    Viedma is a city in northern Patagonia and one of the oldest settlements in Argentina, serving as the capital of Río Negro Province.
  • B. Võru
    Võru is a small town in southeastern Estonia known for its lakeside setting, traditional Võro culture, and role as a regional administrative and cultural center.
  • C. Pääsküla
    Pääsküla is a subdistrict of the Nõmme district in Tallinn, Estonia, known for its residential areas and nearby natural landscapes.
  • D. Jõhvi
    Jõhvi is a town in northeastern Estonia that serves as the administrative center of Ida-Viru County.
  • E. Kraainem
    Kraainem is a Dutch- and French-speaking suburban municipality on the eastern edge of Brussels in the Flemish Brabant province of Belgium.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dd084ff48190ac0f8c46ee722629 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e978b0b481909a531efa030c5def completed April 20, 2026, 8:53 a.m.
Created at: April 10, 2026, 12:06 p.m.