Triple

T18961544
Position Surface form Disambiguated ID Type / Status
Subject Pfeffer E463924 entity
Predicate hasNotableBearer P458 FINISHED
Object Karl Heinz Pfeffer
Karl Heinz Pfeffer is a German individual notable enough to be recognized as a prominent bearer of the surname Pfeffer.
E1942328 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: Karl Heinz Pfeffer | Statement: [Pfeffer, hasNotableBearer, Karl Heinz Pfeffer]
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: Karl Heinz Pfeffer
Triple: [Pfeffer, hasNotableBearer, Karl Heinz Pfeffer]
Generated description
Karl Heinz Pfeffer is a German individual notable enough to be recognized as a prominent bearer of the surname Pfeffer.

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_69d8dcffc278819086792a4ebfddfafa completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d5d2b1c08190a4a32036c70c7746 completed April 20, 2026, 7:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2917ff4e74819093d061c39817969d completed June 10, 2026, 7:53 a.m.
NEDg Description generation batch_6a29197be90c8190bba41e7a1a7f9222 completed June 10, 2026, 7:59 a.m.
NED2 Entity disambiguation (via description) batch_6a291a7f7804819099458886138be398 completed June 10, 2026, 8:04 a.m.
Created at: April 10, 2026, noon