Triple

T2845137
Position Surface form Disambiguated ID Type / Status
Subject Reichsgau Wartheland E62564 entity
Predicate containsCity P294 FINISHED
Object Zgierz
Zgierz is a city in central Poland, historically part of the industrial Łódź region and notable for its textile industry and role in regional trade.
 E496296 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: Zgierz | Statement: [Reichsgau Wartheland, containsCity, Zgierz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zgierz
Context triple: [Reichsgau Wartheland, containsCity, Zgierz]
  • A. Glogów
    Glogów is a historic town in western Poland on the Oder River, known for its medieval origins and reconstructed Old Town.
  • B. Żagań
    Żagań is a town in western Poland known for its historic architecture and its World War II prisoner-of-war camp, Stalag Luft III, site of the “Great Escape.”
  • C. Zduńska Wola
    Zduńska Wola is a town in central Poland known historically as a textile and industrial center.
  • D. Wyszogród
    Wyszogród is a historic town in central Poland on the Vistula River, known for its medieval roots and strategic location that has seen numerous military events over the centuries.
  • E. Parczew
    Parczew is a small town in eastern Poland known for its historical roots and location within the Lublin 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: Zgierz
Triple: [Reichsgau Wartheland, containsCity, Zgierz]
Generated description
Zgierz is a city in central Poland, historically part of the industrial Łódź region and notable for its textile industry and role in regional trade.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zgierz
Target entity description: Zgierz is a city in central Poland, historically part of the industrial Łódź region and notable for its textile industry and role in regional trade.
  • A. Glogów
    Glogów is a historic town in western Poland on the Oder River, known for its medieval origins and reconstructed Old Town.
  • B. Żagań
    Żagań is a town in western Poland known for its historic architecture and its World War II prisoner-of-war camp, Stalag Luft III, site of the “Great Escape.”
  • C. Zduńska Wola
    Zduńska Wola is a town in central Poland known historically as a textile and industrial center.
  • D. Wyszogród
    Wyszogród is a historic town in central Poland on the Vistula River, known for its medieval roots and strategic location that has seen numerous military events over the centuries.
  • E. Parczew
    Parczew is a small town in eastern Poland known for its historical roots and location within the Lublin 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_69ab4c3d16bc81908b3a1c98fbd287fe completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdf1b58c88190b45d8c5a76dc52ac completed March 7, 2026, 8:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69bec330d09c819085930d71b21acb7c completed March 21, 2026, 4:11 p.m.
NEDg Description generation batch_69bec505a5dc81908f79c1ade107c4ce completed March 21, 2026, 4:19 p.m.
NED2 Entity disambiguation (via description) batch_69bec654fc4881909bf5458cdafc7ffd completed March 21, 2026, 4:24 p.m.
Created at: March 6, 2026, 10:02 p.m.