Triple

T18671011
Position Surface form Disambiguated ID Type / Status
Subject SS High Command E456473 entity
Predicate notableCommander P1197 FINISHED
Object Gottlob Berger
Gottlob Berger was a high-ranking Nazi SS official who played a key role in the organization and administration of the Waffen-SS and other SS units during World War II.
E2018166 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: Gottlob Berger | Statement: [SS High Command, notableCommander, Gottlob Berger]
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: Gottlob Berger
Triple: [SS High Command, notableCommander, Gottlob Berger]
Generated description
Gottlob Berger was a high-ranking Nazi SS official who played a key role in the organization and administration of the Waffen-SS and other SS units during World War II.

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_69d8d38f72b4819090a935175d9ca8af completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e556b21d2481908e1b8b583bfabb72 completed April 19, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a349e912c448190b00e68b77c82629d completed June 19, 2026, 1:42 a.m.
NEDg Description generation batch_6a349fe6eff08190a20885913ed7d166 completed June 19, 2026, 1:48 a.m.
NED2 Entity disambiguation (via description) batch_6a34a063b1c481909ae8f34b0988b91a completed June 19, 2026, 1:50 a.m.
Created at: April 10, 2026, 11:48 a.m.