Triple

T13181803
Position Surface form Disambiguated ID Type / Status
Subject Norrland dialects E313746 entity
Predicate hasFeatureVariation P13845 FINISHED
Object strong local variation between provinces LITERAL 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: strong local variation between provinces | Statement: [Norrland dialects, hasFeatureVariation, strong local variation between provinces]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasFeatureVariation
Context triple: [Norrland dialects, hasFeatureVariation, strong local variation between provinces]
  • A. hasVariability chosen
    Indicates that an entity exhibits variation or fluctuation in its state, value, or characteristics over time or across instances.
  • B. hasVariant
    Indicates that one entity exists as an alternative form, version, or variation of another entity.
  • C. hasFeatureCode
    Indicates that an entity is associated with a specific feature identifier or code that characterizes one of its properties or attributes.
  • D. hasServiceVariations
    Indicates that a service is offered in multiple distinct versions, options, or configurations that differ in some defined characteristics.
  • E. hasVariantSystem
    Indicates that one system is an alternative or variant form of another system within the same general framework or category.
  • F. None of above.

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_69d806ae1e08819090d95bfe1538cc17 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98cf054f88190b05ced98d5a22a62 completed April 10, 2026, 11:51 p.m.
PD Predicate disambiguation batch_69d98bc2c0c88190be357811aa8e828d completed April 10, 2026, 11:46 p.m.
Created at: April 9, 2026, 9:15 p.m.