Triple

T6653449
Position Surface form Disambiguated ID Type / Status
Subject Opole Voivodeship (1975–1998) E150879 entity
Predicate containsCity P294 FINISHED
Object Kluczbork
Kluczbork is a town in southern Poland known as a local administrative, cultural, and economic center in the Opole region.
 E848970 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: Kluczbork | Statement: [Opole Voivodeship (1975–1998), containsCity, Kluczbork]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kluczbork
Context triple: [Opole Voivodeship (1975–1998), containsCity, Kluczbork]
  • A. Kociewie
    Kociewie is an ethnocultural region in northern Poland known for its distinct folk traditions, dialect, and rural landscapes.
  • B. Kalisz
    Kalisz is one of Poland’s oldest cities, located in the Greater Poland region and known for its historical architecture and cultural heritage.
  • C. Racibórz
    Racibórz is a historic town in southern Poland, located in the Silesian region near the Czech border, known for its medieval heritage and industrial traditions.
  • D. Glogów
    Glogów is a historic town in western Poland on the Oder River, known for its medieval origins and reconstructed Old Town.
  • E. Zabrze
    Zabrze is an industrial city in the Silesian region of southern Poland, historically known for coal mining and heavy industry.
  • 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: Kluczbork
Triple: [Opole Voivodeship (1975–1998), containsCity, Kluczbork]
Generated description
Kluczbork is a town in southern Poland known as a local administrative, cultural, and economic center in the Opole region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kluczbork
Target entity description: Kluczbork is a town in southern Poland known as a local administrative, cultural, and economic center in the Opole region.
  • A. Kociewie
    Kociewie is an ethnocultural region in northern Poland known for its distinct folk traditions, dialect, and rural landscapes.
  • B. Kalisz
    Kalisz is one of Poland’s oldest cities, located in the Greater Poland region and known for its historical architecture and cultural heritage.
  • C. Racibórz
    Racibórz is a historic town in southern Poland, located in the Silesian region near the Czech border, known for its medieval heritage and industrial traditions.
  • D. Glogów
    Glogów is a historic town in western Poland on the Oder River, known for its medieval origins and reconstructed Old Town.
  • E. Zabrze
    Zabrze is an industrial city in the Silesian region of southern Poland, historically known for coal mining and heavy industry.
  • 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_69c687f2c9508190a60b9aad31d3f358 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b047eb688190bca86be98ac25e39 completed March 27, 2026, 4:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69d55585857c8190a4e4626a92197232 completed April 7, 2026, 7:05 p.m.
NEDg Description generation batch_69d55614368c81909218d3e9d28ef69e completed April 7, 2026, 7:08 p.m.
NED2 Entity disambiguation (via description) batch_69d55669dc788190808b2d99fb9f103c completed April 7, 2026, 7:09 p.m.
Created at: March 27, 2026, 2:01 p.m.