Triple

T17777159
Position Surface form Disambiguated ID Type / Status
Subject Diguillín Province E443800 entity
Predicate hasTown P847 FINISHED
Object Yungay 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: Yungay | Statement: [Diguillín Province, hasTown, Yungay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yungay
Context triple: [Diguillín Province, hasTown, Yungay]
  • A. Yungay chosen
    Yungay is a small Chilean city located in the Ñuble Region, known for its agricultural surroundings and Andean foothill landscapes.
  • B. Yungay
    Yungay is a town in north-central Peru known for being devastated by a catastrophic earthquake and landslide in 1970, after which a new settlement was built nearby.
  • C. Gelmeroda
    Gelmeroda is a small village near Weimar in Germany, best known for its church, which was repeatedly depicted in a series of paintings by the modernist artist Lyonel Feininger.
  • D. Vedelago
    Vedelago is a municipality in the Veneto region of northern Italy, known for its historic villas and rural landscape.
  • E. Yilgarn
    Yilgarn is a rural town and shire in Western Australia known for its grain farming and mining activities within the Wheatbelt region.
  • 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_69d8b9ef17708190bdf7e2adbf14ddc2 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4871e06a481909cf6d59e49dc21c5 completed April 19, 2026, 7:41 a.m.
Created at: April 10, 2026, 10:12 a.m.