Triple

T27187790
Position Surface form Disambiguated ID Type / Status
Subject Henryk Mikołaj Górecki E683383 entity
Predicate hasChild P369 FINISHED
Object Mikołaj Górecki
Mikołaj Górecki is a Polish composer and the son of renowned composer Henryk Mikołaj Górecki, known for his own contributions to contemporary classical music.
E1771594 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: Mikołaj Górecki | Statement: [Henryk Mikołaj Górecki, hasChild, Mikołaj Górecki]
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: Mikołaj Górecki
Triple: [Henryk Mikołaj Górecki, hasChild, Mikołaj Górecki]
Generated description
Mikołaj Górecki is a Polish composer and the son of renowned composer Henryk Mikołaj Górecki, known for his own contributions to contemporary classical music.

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_69eefad140408190b8586fdebcf9af46 completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f625a8e3e881908191d1b0e08030a0 completed May 2, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12b222e4208190b14f05f9223aa8e2 completed May 24, 2026, 8:09 a.m.
NEDg Description generation batch_6a12b2c102b881908d0c1299f6e1035d completed May 24, 2026, 8:11 a.m.
NED2 Entity disambiguation (via description) batch_6a12b33dc9f881908cca1fd1b03c6c67 completed May 24, 2026, 8:13 a.m.
Created at: April 27, 2026, 9:31 a.m.