Triple

T6338237
Position Surface form Disambiguated ID Type / Status
Subject GKS E142549 entity
Predicate associatedWithCountyOrCity P19735 FINISHED
Object Słupsk E178809 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: Słupsk | Statement: [GKS, associatedWithCountyOrCity, Słupsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Słupsk
Context triple: [GKS, associatedWithCountyOrCity, Słupsk]
  • A. Słupsk chosen
    Słupsk is a historic city in northern Poland known for its medieval architecture and location near the Baltic Sea.
  • B. Koszalin
    Koszalin is a city in northwestern Poland near the Baltic Sea, known as a regional cultural and economic center.
  • C. Świdwin
    Świdwin is a historic town in northwestern Poland, known for its medieval castle and location in the West Pomeranian Voivodeship.
  • D. Świnoujście
    Świnoujście is a Polish port city and seaside resort on the Baltic Sea, known for its wide beaches, spa facilities, and strategic location at the mouth of the Świna River.
  • E. Giżycko
    Giżycko is a popular lakeside town in northeastern Poland, known as a major sailing and tourism center in the Masurian Lake District.
  • 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: associatedWithCountyOrCity
Context triple: [GKS, associatedWithCountyOrCity, Słupsk]
  • A. associatedWithCounty
    Indicates that an entity has a relationship or linkage to a specific county, such as jurisdiction, location, or administrative association.
  • B. associatedWithLocality chosen
    Indicates a relationship where something has a connection or relevance to a specific geographic place or locality.
  • C. hasAssociatedCity
    Indicates that one entity is linked or related to a specific city, typically as its location, base, or primary area of association.
  • D. isInCountySeatOf
    Indicates that one entity is located within the town or city that serves as the administrative center (county seat) of a specified county.
  • E. associatedWithSubdivision
    Indicates that one entity has a connection or linkage to a specific administrative or organizational subdivision.
  • 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_69c008d4d8e88190ad301c05b08722ac completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0654e11988190b708426d3003716a completed March 22, 2026, 9:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c922a0d2688190982714e2e409465d completed March 29, 2026, 1:01 p.m.
PD Predicate disambiguation batch_69c060e7e2d48190af9d004236466788 completed March 22, 2026, 9:36 p.m.
Created at: March 22, 2026, 4:30 p.m.