Triple

T33357481
Position Surface form Disambiguated ID Type / Status
Subject Kaczmarek E854115 entity
Predicate usedBy P260 FINISHED
Object Marek Kaczmarek
Marek Kaczmarek is a Polish former professional footballer who became a football manager.
E2183125 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: Marek Kaczmarek | Statement: [Kaczmarek, usedBy, Marek 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: Marek Kaczmarek
Triple: [Kaczmarek, usedBy, Marek Kaczmarek]
Generated description
Marek Kaczmarek is a Polish former professional footballer who became a football manager.

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_6a39c3d55c908190a59ddb6d80a4f8fa completed June 22, 2026, 11:23 p.m.
NEDg Description generation batch_6a39c48912548190bd632d5e355f3cb2 completed June 22, 2026, 11:26 p.m.
NED2 Entity disambiguation (via description) batch_6a39c55c9d188190b9a5dab4ca8036e8 completed June 22, 2026, 11:29 p.m.
Created at: May 1, 2026, 1:34 a.m.