Triple

T18920037
Position Surface form Disambiguated ID Type / Status
Subject Piekary Śląskie E462825 entity
Predicate formedByMergerOf P77 FINISHED
Object Szarlej
Szarlej is a former locality in southern Poland that was incorporated into the city of Piekary Śląskie as part of its municipal formation.
 E1349566 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: Szarlej | Statement: [Piekary Śląskie, formedByMergerOf, Szarlej]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Szarlej
Context triple: [Piekary Śląskie, formedByMergerOf, Szarlej]
  • A. Raszar
    Raszar is a cinematographer known for his work on the film "Human Traffic."
  • B. Muraz
    Muraz is a village and locality within the municipality of Collombey-Muraz in the canton of Valais, Switzerland.
  • C. Zaleski
    Zaleski is a Polish surname most notably borne by August Zaleski, a prominent Polish diplomat and statesman who served as President of Poland in exile.
  • D. Łuck
    Łuck is the Polish name for Lutsk, a historic city in western Ukraine known for its medieval castle and role as a regional cultural center.
  • E. Sylwka
    Sylwka is a Polish diminutive form of the female given name Sylwia, used as an affectionate or informal nickname.
  • 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: Szarlej
Triple: [Piekary Śląskie, formedByMergerOf, Szarlej]
Generated description
Szarlej is a former locality in southern Poland that was incorporated into the city of Piekary Śląskie as part of its municipal formation.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Szarlej
Target entity description: Szarlej is a former locality in southern Poland that was incorporated into the city of Piekary Śląskie as part of its municipal formation.
  • A. Raszar
    Raszar is a cinematographer known for his work on the film "Human Traffic."
  • B. Muraz
    Muraz is a village and locality within the municipality of Collombey-Muraz in the canton of Valais, Switzerland.
  • C. Zaleski
    Zaleski is a Polish surname most notably borne by August Zaleski, a prominent Polish diplomat and statesman who served as President of Poland in exile.
  • D. Łuck
    Łuck is the Polish name for Lutsk, a historic city in western Ukraine known for its medieval castle and role as a regional cultural center.
  • E. Sylwka
    Sylwka is a Polish diminutive form of the female given name Sylwia, used as an affectionate or informal nickname.
  • 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_69d8dcfdbbb881909964fa5a75bd0b48 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c62a264c81909f6d5df841486efc completed April 20, 2026, 6:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a059118f1608190ad84f5da69b86a50 completed May 14, 2026, 9:08 a.m.
NEDg Description generation batch_6a0593141058819091183ede1dd0b878 completed May 14, 2026, 9:17 a.m.
NED2 Entity disambiguation (via description) batch_6a059439ee6c8190beb258f70385ee82 completed May 14, 2026, 9:22 a.m.
Created at: April 10, 2026, 11:59 a.m.