Triple

T35056456
Position Surface form Disambiguated ID Type / Status
Subject Wirtschafts- und Verwaltungshauptamt E1011478 entity
Predicate hasPart P35 FINISHED
Object Amtsgruppe C
Amtsgruppe C was a department within the SS Main Economic and Administrative Office (WVHA) responsible primarily for construction and infrastructure matters in Nazi Germany.
E2125829 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: Amtsgruppe C | Statement: [Wirtschafts- und Verwaltungshauptamt, hasPart, Amtsgruppe C]
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: Amtsgruppe C
Triple: [Wirtschafts- und Verwaltungshauptamt, hasPart, Amtsgruppe C]
Generated description
Amtsgruppe C was a department within the SS Main Economic and Administrative Office (WVHA) responsible primarily for construction and infrastructure matters in Nazi Germany.

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_69f76dd09c308190a523454853ce842b completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f785d16e3c819093d8324e3abea629 completed May 3, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37cfe198fc81909bea21d760c5a0f7 completed June 21, 2026, 11:49 a.m.
NEDg Description generation batch_6a37d07ba708819081b552b8a69313e5 completed June 21, 2026, 11:52 a.m.
NED2 Entity disambiguation (via description) batch_6a37d1935d9881909cee3755fec2d996 completed June 21, 2026, 11:57 a.m.
Created at: May 3, 2026, 4:01 p.m.