Triple

T37329340
Position Surface form Disambiguated ID Type / Status
Subject House of Mansfeld E926698 entity
Predicate hasCadetBranch P2906 FINISHED
Object Mansfeld-Arnstein
Mansfeld-Arnstein was a cadet branch of the German noble House of Mansfeld, associated with territorial holdings and aristocratic lineage in the region of Mansfeld.
E2226506 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: Mansfeld-Arnstein | Statement: [House of Mansfeld, hasCadetBranch, Mansfeld-Arnstein]
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: Mansfeld-Arnstein
Triple: [House of Mansfeld, hasCadetBranch, Mansfeld-Arnstein]
Generated description
Mansfeld-Arnstein was a cadet branch of the German noble House of Mansfeld, associated with territorial holdings and aristocratic lineage in the region of Mansfeld.

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_6a40823c560081908d137a2108e1703e completed June 28, 2026, 2:09 a.m.
NEDg Description generation batch_6a4083266990819092378557ff164ce0 completed June 28, 2026, 2:12 a.m.
NED2 Entity disambiguation (via description) batch_6a4083cb3a90819082ec8d56067094a0 completed June 28, 2026, 2:15 a.m.
Created at: May 3, 2026, 4:16 p.m.