Triple

T12080854
Position Surface form Disambiguated ID Type / Status
Subject Rolle E287672 entity
Predicate hasNeighboringMunicipality P224 FINISHED
Object Gland E437776 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: Gland | Statement: [Rolle, hasNeighboringMunicipality, Gland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gland
Context triple: [Rolle, hasNeighboringMunicipality, Gland]
  • A. Gland chosen
    Gland is a Swiss municipality in the canton of Vaud, situated on the shores of Lake Geneva between Geneva and Lausanne.
  • B. Glandyfi
    Glandyfi is a small hamlet in Ceredigion, Wales, known for its scenic setting near the River Dovey and the Cambrian Coast railway line.
  • C. Grove
    Grove is a large village and civil parish in Oxfordshire, England, situated near Wantage and known for its residential communities and local amenities.
  • D. Grove
    Grove is an unincorporated community in James City County, Virginia, known for its residential areas and proximity to historic Williamsburg and the James River.
  • E. Grove
    Grove is a surname most prominently associated with Andrew S. Grove, the influential engineer and former CEO of Intel who helped shape the modern semiconductor industry.
  • 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_69d6ab4964708190850585628b287b0c completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d904dc98a88190a5873f3fd8e1a0b2 completed April 10, 2026, 2:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f66301f081909697f9dd444a099e completed May 2, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:48 p.m.