Triple

T11736753
Position Surface form Disambiguated ID Type / Status
Subject Ringsted E279045 entity
Predicate hasNearbyCity P350 FINISHED
Object Sorø E850344 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: Sorø | Statement: [Ringsted, hasNearbyCity, Sorø]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sorø
Context triple: [Ringsted, hasNearbyCity, Sorø]
  • A. Sorø chosen
    Sorø is a historic Danish town on the island of Zealand, known for its medieval abbey, prestigious Sorø Academy, and scenic lakeside setting.
  • B. Sønderborg
    Sønderborg is a coastal town in southern Denmark known for its historic castle, waterfront setting on the island of Als, and role as a regional cultural and educational center.
  • C. Thisted
    Thisted is a coastal town and municipality in northwestern Jutland, Denmark, known for its scenic location by the Limfjord and its role as a regional commercial and cultural center.
  • D. Oksbøl
    Oksbøl is a town in southwestern Jutland, Denmark, known for its military training areas and historical role as a garrison location.
  • E. Søborg
    Søborg is a Danish surname most notably borne by individuals such as cinematographer Morten Søborg.
  • 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4edced48190b7a59dd45921828e completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f16679c0ec81909fe80d75dd582db1 completed April 29, 2026, 2:01 a.m.
Created at: April 8, 2026, 9:41 p.m.