Triple

T9336573
Position Surface form Disambiguated ID Type / Status
Subject KS Toruń (speedway) E224657 entity
Predicate formerName P65 FINISHED
Object Get Well Toruń
Get Well Toruń was the former sponsored name of the Polish speedway club KS Toruń, a prominent team in the national speedway league.
E793806 NE FINISHED

How this triple was built (4 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: Get Well Toruń | Statement: [KS Toruń (speedway), formerName, Get Well Toruń]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Get Well Toruń
Context triple: [KS Toruń (speedway), formerName, Get Well Toruń]
  • A. Dobre Miasto
    Dobre Miasto is a small historic town in northern Poland known for its medieval architecture and location within the picturesque Warmia region.
  • B. Białka Tatrzańska
    Białka Tatrzańska is a popular mountain village and ski resort in southern Poland, known for its thermal baths and access to the Tatra Mountains.
  • C. Tuszów Narodowy
    Tuszów Narodowy is a village in southeastern Poland best known as the birthplace of General Władysław Sikorski, a prominent Polish military and political leader.
  • D. Gołąbki
    Gołąbki is a locality in Poland known historically as the place where former Polish president Stanisław Wojciechowski died.
  • E. Sokółka
    Sokółka is a small town in northeastern Poland known for its location in the Podlasie region near the border with Belarus.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Get Well Toruń
Triple: [KS Toruń (speedway), formerName, Get Well Toruń]
Generated description
Get Well Toruń was the former sponsored name of the Polish speedway club KS Toruń, a prominent team in the national speedway league.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Get Well Toruń
Target entity description: Get Well Toruń was the former sponsored name of the Polish speedway club KS Toruń, a prominent team in the national speedway league.
  • A. Dobre Miasto
    Dobre Miasto is a small historic town in northern Poland known for its medieval architecture and location within the picturesque Warmia region.
  • B. Białka Tatrzańska
    Białka Tatrzańska is a popular mountain village and ski resort in southern Poland, known for its thermal baths and access to the Tatra Mountains.
  • C. Tuszów Narodowy
    Tuszów Narodowy is a village in southeastern Poland best known as the birthplace of General Władysław Sikorski, a prominent Polish military and political leader.
  • D. Gołąbki
    Gołąbki is a locality in Poland known historically as the place where former Polish president Stanisław Wojciechowski died.
  • E. Sokółka
    Sokółka is a small town in northeastern Poland known for its location in the Podlasie region near the border with Belarus.
  • F. None of above. chosen

Provenance (5 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_69ca84286fcc81909f6e7fd7a7e862a2 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd37f161e481908e23c1ec7e5fcf97 completed April 1, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0e3d8316081908cb9ea36eb069c2d completed April 4, 2026, 10:11 a.m.
NEDg Description generation batch_69d0e57272cc819085a1fd3e356d7c46 completed April 4, 2026, 10:18 a.m.
NED2 Entity disambiguation (via description) batch_69d0e72c3d088190953a5929f8b861d8 completed April 4, 2026, 10:25 a.m.
Created at: March 30, 2026, 7:40 p.m.