Triple

T13049786
Position Surface form Disambiguated ID Type / Status
Subject Czersk Piasts E327420 entity
Predicate centeredIn P4751 FINISHED
Object Czersk
Czersk is a town in northern Poland known for its location in the Pomeranian Voivodeship and its historical ties to regional noble lineages.
E1236019 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: Czersk | Statement: [Czersk Piasts, centeredIn, Czersk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Czersk
Context triple: [Czersk Piasts, centeredIn, Czersk]
  • A. Czorsztyn
    Czorsztyn is a small village in southern Poland known for its picturesque lakeside setting on the Dunajec River and the ruins of a medieval castle overlooking the Pieniny Mountains.
  • B. Chrzanów
    Chrzanów is a town in southern Poland known for its historical architecture and role as a local industrial and administrative center.
  • C. Chorobrów
    Chorobrów is a village in western Ukraine, historically part of the region of Galicia.
  • D. Skrzyczne
    Skrzyczne is a prominent mountain in southern Poland known for its hiking trails, ski resort, and panoramic views over the Silesian Beskids.
  • E. Choszczno
    Choszczno is a small town in northwestern Poland known for its lakes, forests, and role as a local administrative and service center.
  • 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: Czersk
Triple: [Czersk Piasts, centeredIn, Czersk]
Generated description
Czersk is a town in northern Poland known for its location in the Pomeranian Voivodeship and its historical ties to regional noble lineages.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Czersk
Target entity description: Czersk is a town in northern Poland known for its location in the Pomeranian Voivodeship and its historical ties to regional noble lineages.
  • A. Czorsztyn
    Czorsztyn is a small village in southern Poland known for its picturesque lakeside setting on the Dunajec River and the ruins of a medieval castle overlooking the Pieniny Mountains.
  • B. Chrzanów
    Chrzanów is a town in southern Poland known for its historical architecture and role as a local industrial and administrative center.
  • C. Chorobrów
    Chorobrów is a village in western Ukraine, historically part of the region of Galicia.
  • D. Skrzyczne
    Skrzyczne is a prominent mountain in southern Poland known for its hiking trails, ski resort, and panoramic views over the Silesian Beskids.
  • E. Choszczno
    Choszczno is a small town in northwestern Poland known for its lakes, forests, and role as a local administrative and service center.
  • 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_69d8076e64308190904fb5c93517c901 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d980b8811c81908577f092e2736610 completed April 10, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00baf8a2648190adf3ad3af118187f completed May 10, 2026, 5:06 p.m.
NEDg Description generation batch_6a00bbb628208190b0be62a333e7e442 completed May 10, 2026, 5:09 p.m.
NED2 Entity disambiguation (via description) batch_6a00bc3a4b888190bd190b9330e2777d completed May 10, 2026, 5:11 p.m.
Created at: April 9, 2026, 8:57 p.m.