Triple

T9496125
Position Surface form Disambiguated ID Type / Status
Subject Savosavo language E229008 entity
Predicate hasAlternativeName P39 FINISHED
Object Savo E678045 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: Savo | Statement: [Savosavo language, hasAlternativeName, Savo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Savo
Context triple: [Savosavo language, hasAlternativeName, Savo]
  • A. Savo chosen
    Savo is a historical and cultural region in eastern Finland known for its lakes, forests, and distinctive Savonian dialect and traditions.
  • B. Savo
    Savo is a town in Kenya’s Central Province known as one of the region’s notable settlements.
  • C. Samoggia
    Samoggia is a river in the Emilia-Romagna region of northern Italy that flows through the provinces of Bologna and Modena before joining the Panaro.
  • D. Fiumelatte
    Fiumelatte is a small Italian village on Lake Como known for its short, seasonally flowing “milk-colored” river, considered one of the shortest rivers in Italy.
  • E. Morava
    Morava is a Central European river that forms part of the border between Austria, the Czech Republic, and Slovakia before joining the Danube near Bratislava.
  • 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_69ca84753660819098e8d416e89e26ae completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd95eb87b081908fc7255598cd9a24 completed April 1, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69d12d34967881909980be6f1be80885 completed April 4, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:56 p.m.