Triple

T25810547
Position Surface form Disambiguated ID Type / Status
Subject Schiffer E650094 entity
Predicate hasNotableBearer P458 FINISHED
Object Herbert Schiffer
Herbert Schiffer is an individual notable enough to be recognized as a namesake bearer of the surname Schiffer.
E2288722 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: Herbert Schiffer | Statement: [Schiffer, hasNotableBearer, Herbert Schiffer]
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: Herbert Schiffer
Triple: [Schiffer, hasNotableBearer, Herbert Schiffer]
Generated description
Herbert Schiffer is an individual notable enough to be recognized as a namesake bearer of the surname Schiffer.

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_69e7ab35d264819095367f7e80c983ff completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f600c37d40819086cc056057c25629 completed May 2, 2026, 1:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5ad71b60008190906b4ad76ae76a36 completed July 18, 2026, 1:30 a.m.
NEDg Description generation batch_6a5ad82f2cc48190bd8d8a49a2d410a0 completed July 18, 2026, 1:34 a.m.
NED2 Entity disambiguation (via description) batch_6a5ad886e008819086121eadc086217b completed July 18, 2026, 1:36 a.m.
Created at: April 22, 2026, 7:09 a.m.