Triple

T36516740
Position Surface form Disambiguated ID Type / Status
Subject Bergmann E900057 entity
Predicate hasNotableBearer P458 FINISHED
Object Paul Bergmann
Paul Bergmann is a relatively obscure individual whose primary distinguishing feature in this context is sharing the surname Bergmann, which is borne by several more widely known figures in fields such as physics and philosophy.
E2208052 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: Paul Bergmann | Statement: [Bergmann, hasNotableBearer, Paul Bergmann]
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: Paul Bergmann
Triple: [Bergmann, hasNotableBearer, Paul Bergmann]
Generated description
Paul Bergmann is a relatively obscure individual whose primary distinguishing feature in this context is sharing the surname Bergmann, which is borne by several more widely known figures in fields such as physics and philosophy.

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_69f76e5dada881909da2d34bc7a9202a completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7c1f387608190984b4f57c5c973ae completed May 3, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e57407f7c819090b5d03b5b7d182b completed June 26, 2026, 10:41 a.m.
NEDg Description generation batch_6a3e591d57608190bd82a60c74d1ae1d completed June 26, 2026, 10:49 a.m.
NED2 Entity disambiguation (via description) batch_6a3e5f4a910081908f9ff844c1feb1ae completed June 26, 2026, 11:15 a.m.
Created at: May 3, 2026, 4:11 p.m.