Triple

T22919687
Position Surface form Disambiguated ID Type / Status
Subject Mack family E568825 entity
Predicate hasMember P10 FINISHED
Object Jürgen Mack
Jürgen Mack is a German businessman and co-owner of Europa-Park, one of Europe’s largest theme parks, operated by the Mack family.
E2196010 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: Jürgen Mack | Statement: [Mack family, hasMember, Jürgen Mack]
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: Jürgen Mack
Triple: [Mack family, hasMember, Jürgen Mack]
Generated description
Jürgen Mack is a German businessman and co-owner of Europa-Park, one of Europe’s largest theme parks, operated by the Mack family.

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_69e2458d90c88190a58cead4e781ca6a completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f180d316188190901d9356c07110e3 completed April 29, 2026, 3:53 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3a37fe85c48190a3e652d2543268ad completed June 23, 2026, 7:38 a.m.
NEDg Description generation batch_6a3a388b449c8190b3ded5a3a91dacfa completed June 23, 2026, 7:40 a.m.
NED2 Entity disambiguation (via description) batch_6a3a414e220c819093a0f0611a24df52 completed June 23, 2026, 8:18 a.m.
Created at: April 17, 2026, 3:42 p.m.