Triple

T31684066
Position Surface form Disambiguated ID Type / Status
Subject Leipzig Book Award for European Understanding E808607 entity
Predicate notableLaureate P1618 FINISHED
Object Karl Schlögel
Karl Schlögel is a German historian and author renowned for his works on Eastern Europe, Russian history, and the cultural and spatial history of the 20th century.
E2293683 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: Karl Schlögel | Statement: [Leipzig Book Award for European Understanding, notableLaureate, Karl Schlögel]
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: Karl Schlögel
Triple: [Leipzig Book Award for European Understanding, notableLaureate, Karl Schlögel]
Generated description
Karl Schlögel is a German historian and author renowned for his works on Eastern Europe, Russian history, and the cultural and spatial history of the 20th century.

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_69f348dcf5d48190ac25b1365ae717a8 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6aa7a94a08190a6cdb1f08bf8e2b5 completed May 3, 2026, 1:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a7af02e29488190bad8ff1a966cb042 completed Aug. 11, 2026, 9:49 a.m.
NEDg Description generation batch_6a7af093e43081908a1ed93ffea4620a completed Aug. 11, 2026, 9:51 a.m.
NED2 Entity disambiguation (via description) batch_6a7af100e31c8190bde42e0cd9442381 completed Aug. 11, 2026, 9:53 a.m.
Created at: April 30, 2026, 11:06 p.m.