Triple

T15558013
Position Surface form Disambiguated ID Type / Status
Subject Vrbas E370919 entity
Predicate hasValley P650 FINISHED
Object Vrbas valley E370919 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: Vrbas valley | Statement: [Vrbas, hasValley, Vrbas valley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vrbas valley
Context triple: [Vrbas, hasValley, Vrbas valley]
  • A. Kočani Valley
    Kočani Valley is a fertile agricultural valley in eastern North Macedonia, known especially for its rice fields and surrounding mountainous landscape.
  • B. Nišava Valley
    Nišava Valley is a geographic region in southeastern Europe shaped by the course of the Nišava River, known for its strategic transport routes and surrounding mountainous landscapes.
  • C. Vrbas
    Vrbas is a town and municipality in the Bačka region of northern Serbia, known as a local administrative, industrial, and transportation center.
  • D. Vrbas chosen
    Vrbas is a river in western Bosnia and Herzegovina that flows through cities like Banja Luka before joining the Sava River.
  • E. Vipava Valley
    Vipava Valley is a picturesque wine-growing region in western Slovenia known for its mild climate, karst landscapes, and historic villages.
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04dda3ab88190ab383333ce69fe8f completed April 16, 2026, 2:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff56bf8cac81909886de5b82849cb2 completed May 9, 2026, 3:46 p.m.
Created at: April 10, 2026, 4:09 a.m.