Triple

T33357484
Position Surface form Disambiguated ID Type / Status
Subject Kaczmarek E854115 entity
Predicate usedBy P260 FINISHED
Object Jerzy Kaczmarek
Jerzy Kaczmarek is a Polish individual whose name appears in reference data but for whom no widely documented public biography or notable achievements are readily available.
E2284747 NE FINISHED

How this triple was built (2 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: Jerzy Kaczmarek | Statement: [Kaczmarek, usedBy, Jerzy Kaczmarek]
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: Jerzy Kaczmarek
Triple: [Kaczmarek, usedBy, Jerzy Kaczmarek]
Generated description
Jerzy Kaczmarek is a Polish individual whose name appears in reference data but for whom no widely documented public biography or notable achievements are readily available.

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_69f3496acbc8819099fd0305ecc42080 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6dfa2637c81908d01d8ccfa4a9d54 completed May 3, 2026, 5:39 a.m.
NED1 Entity disambiguation (via context triple) batch_6a43e9cf9a00819083a38703f514335a completed June 30, 2026, 4:07 p.m.
NEDg Description generation batch_6a43ef00a35c8190a7259605ea2fd60a completed June 30, 2026, 4:29 p.m.
NED2 Entity disambiguation (via description) batch_6a449f54c104819089cb9590689ab18a completed July 1, 2026, 5:02 a.m.
Created at: May 1, 2026, 1:34 a.m.