Triple

T33277909
Position Surface form Disambiguated ID Type / Status
Subject Polish reportage school E851953 entity
Predicate notableAuthor P4290 FINISHED
Object Krzysztof Kąkolewski
Krzysztof Kąkolewski was a prominent Polish journalist and writer, regarded as one of the pioneers and masters of modern Polish literary reportage.
E2178784 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: Krzysztof Kąkolewski | Statement: [Polish reportage school, notableAuthor, Krzysztof Kąkolewski]
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: Krzysztof Kąkolewski
Triple: [Polish reportage school, notableAuthor, Krzysztof Kąkolewski]
Generated description
Krzysztof Kąkolewski was a prominent Polish journalist and writer, regarded as one of the pioneers and masters of modern Polish literary reportage.

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_69f349653da08190819876015a298fdb completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6de44c8e48190a7620b98cd8d7723 completed May 3, 2026, 5:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a397d5fb7e0819097e50cdcbc3f16e5 completed June 22, 2026, 6:22 p.m.
NEDg Description generation batch_6a3982048b2c81908600ba0a88de55e9 completed June 22, 2026, 6:42 p.m.
NED2 Entity disambiguation (via description) batch_6a39853c4d84819092fccb609d8c5195 completed June 22, 2026, 6:55 p.m.
Created at: May 1, 2026, 1:32 a.m.