Triple

T6294162
Position Surface form Disambiguated ID Type / Status
Subject Eckert E141088 entity
Predicate hasNotableBearer P458 FINISHED
Object Günter Eckert
Günter Eckert is a notable individual who shares the surname Eckert and is recognized as a distinguished bearer of that name.
E2297517 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: Günter Eckert | Statement: [Eckert, hasNotableBearer, Günter Eckert]
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: Günter Eckert
Triple: [Eckert, hasNotableBearer, Günter Eckert]
Generated description
Günter Eckert is a notable individual who shares the surname Eckert and is recognized as a distinguished bearer of that name.

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_69c008cdf2ac8190bb640c94478fb4ed completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06438654481908c9833c5f0d61773 completed March 22, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a8390860fd48190b7e09bca7d3545fe completed Aug. 17, 2026, 10:51 p.m.
NEDg Description generation batch_6a8391005f208190974549957dcf8c16 completed Aug. 17, 2026, 10:53 p.m.
NED2 Entity disambiguation (via description) batch_6a839151a82481909300d8bd2507da1d completed Aug. 17, 2026, 10:55 p.m.
Created at: March 22, 2026, 4:27 p.m.