Triple

T5943504
Position Surface form Disambiguated ID Type / Status
Subject Jelgava E132222 entity
Predicate hasTwinTown P919 FINISHED
Object Kędzierzyn-Koźle
Kędzierzyn-Koźle is a town in southern Poland known as an important industrial and river port center on the Oder River.
 E692052 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: Kędzierzyn-Koźle | Statement: [Jelgava, hasTwinTown, Kędzierzyn-Koźle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kędzierzyn-Koźle
Context triple: [Jelgava, hasTwinTown, Kędzierzyn-Koźle]
  • A. Kociewie
    Kociewie is an ethnocultural region in northern Poland known for its distinct folk traditions, dialect, and rural landscapes.
  • B. Chorzów
    Chorzów is an industrial city in southern Poland’s Silesian region, known for its heavy industry heritage and the extensive Silesian Park.
  • C. Glogów
    Glogów is a historic town in western Poland on the Oder River, known for its medieval origins and reconstructed Old Town.
  • D. Skierniewice
    Skierniewice is a historic city in central Poland known for its horticultural research center and annual Skierniewice Fruit and Vegetable Festival.
  • E. Polkowice
    Polkowice is a town in southwestern Poland known for its copper mining industry and location within the Lower Silesian region.
  • 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: Kędzierzyn-Koźle
Triple: [Jelgava, hasTwinTown, Kędzierzyn-Koźle]
Generated description
Kędzierzyn-Koźle is a town in southern Poland known as an important industrial and river port center on the Oder River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kędzierzyn-Koźle
Target entity description: Kędzierzyn-Koźle is a town in southern Poland known as an important industrial and river port center on the Oder River.
  • A. Kociewie
    Kociewie is an ethnocultural region in northern Poland known for its distinct folk traditions, dialect, and rural landscapes.
  • B. Chorzów
    Chorzów is an industrial city in southern Poland’s Silesian region, known for its heavy industry heritage and the extensive Silesian Park.
  • C. Glogów
    Glogów is a historic town in western Poland on the Oder River, known for its medieval origins and reconstructed Old Town.
  • D. Skierniewice
    Skierniewice is a historic city in central Poland known for its horticultural research center and annual Skierniewice Fruit and Vegetable Festival.
  • E. Polkowice
    Polkowice is a town in southwestern Poland known for its copper mining industry and location within the Lower Silesian region.
  • 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_69c00869d3308190af89b2453e0f7546 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0393641d0819081c6c44816d94e4e completed March 22, 2026, 6:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9d13a8b108190a0b13592f3a6362e completed March 30, 2026, 1:26 a.m.
NEDg Description generation batch_69c9d44d0d2881909f4ed7af19ae5f02 completed March 30, 2026, 1:39 a.m.
NED2 Entity disambiguation (via description) batch_69c9d4cab81081908c374a250e9f3fa2 completed March 30, 2026, 1:41 a.m.
Created at: March 22, 2026, 4:01 p.m.