Triple

T790638
Position Surface form Disambiguated ID Type / Status
Subject Jura E16904 entity
Predicate hasMunicipalities P747 FINISHED
Object Delémont E161079 NE FINISHED

How this triple was built (3 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: Delémont | Statement: [Jura, hasMunicipalities, Delémont]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Delémont
Context triple: [Jura, hasMunicipalities, Delémont]
  • A. Delémont chosen
    Delémont is a historic town in northwestern Switzerland that serves as the capital of the canton of Jura.
  • B. Hermance
    Hermance is a small lakeside municipality on the shores of Lake Geneva in southwestern Switzerland.
  • C. Martigny
    Martigny is a historic town in southwestern Switzerland known as a cultural and transportation hub in the canton of Valais, near the Great St. Bernard Pass.
  • D. Cluses
    Cluses is a small industrial town in southeastern France known for its precision engineering and watchmaking heritage, located in the Arve Valley of the Haute-Savoie department in the Alps.
  • E. Bardonnex
    Bardonnex is a small Swiss municipality located in the canton of Geneva, near the country’s border with France.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMunicipalities
Context triple: [Jura, hasMunicipalities, Delémont]
  • A. hasMunicipalGovernment
    Indicates that an entity is administered or governed by a municipal-level governmental authority.
  • B. hasMunicipalityType
    Indicates that an administrative unit is classified as having a specific type or category of municipality (e.g., city, town, village).
  • C. hasMunicipalSections
    Indicates that a municipality is divided into and associated with specific internal administrative sections or districts.
  • D. spansMunicipality
    Indicates that something (such as an area, structure, or feature) extends across or covers more than one municipality.
  • E. hasSubdivision chosen
    Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
  • F. None of above.

Provenance (4 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_69a4936cb7448190914f5fe4b8d81607 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a79754988190ab494b1c54d6a2a4 completed March 1, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad15866b448190b20334eddca756eb completed March 8, 2026, 6:21 a.m.
PD Predicate disambiguation batch_69a4a50ef72c819084ffe9f31dbd0262 completed March 1, 2026, 8:43 p.m.
Created at: March 1, 2026, 7:38 p.m.