Triple

T37329329
Position Surface form Disambiguated ID Type / Status
Subject House of Mansfeld E926698 entity
Predicate hasNotableMember P304 FINISHED
Object Albrecht von Mansfeld
Albrecht von Mansfeld was a notable German nobleman from the influential House of Mansfeld, active during the late medieval to early modern period in central Europe.
E2224949 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: Albrecht von Mansfeld | Statement: [House of Mansfeld, hasNotableMember, Albrecht von Mansfeld]
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: Albrecht von Mansfeld
Triple: [House of Mansfeld, hasNotableMember, Albrecht von Mansfeld]
Generated description
Albrecht von Mansfeld was a notable German nobleman from the influential House of Mansfeld, active during the late medieval to early modern period in central Europe.

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_69f76eb386d88190a8d511aa11540dfc completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb5b68fa3c8190832230e7c8a4e463 completed May 6, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4076ed34148190a2cd8c01987ee867 completed June 28, 2026, 1:20 a.m.
NEDg Description generation batch_6a4077c183048190b60204779b4336b5 completed June 28, 2026, 1:24 a.m.
NED2 Entity disambiguation (via description) batch_6a4078362d0881909b963ee3fe45787e completed June 28, 2026, 1:26 a.m.
Created at: May 3, 2026, 4:16 p.m.