Triple

T20940199
Position Surface form Disambiguated ID Type / Status
Subject Praz E515697 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Sugiez 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: Sugiez | Statement: [Praz, hasNearbySettlement, Sugiez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sugiez
Context triple: [Praz, hasNearbySettlement, Sugiez]
  • A. Sugiez chosen
    Sugiez is a small village in the canton of Fribourg, Switzerland, situated in the scenic Vully region near Lake Murten.
  • B. Odiongan
    Odiongan is a coastal municipality on Tablas Island in Romblon province, Philippines, serving as a local commercial and transportation hub in the region.
  • C. Mattawa
    Mattawa is a small town in northeastern Ontario, Canada, located at the confluence of the Mattawa and Ottawa Rivers and known historically as a key fur trade and logging route.
  • D. Vilas
    Vilas is the surname of Guillermo Vilas, the legendary Argentine tennis player renowned for his clay-court dominance in the 1970s.
  • E. Bois Blancs
    Bois Blancs is a metro station in Lille, France, serving the city's automated Line 2 transit route.
  • 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_69e0b4fc13408190b06868df03c5c29b completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6f954e44481909098a0b23a687d5e completed April 21, 2026, 4:13 a.m.
Created at: April 16, 2026, 12:50 p.m.