Triple

T36306616
Position Surface form Disambiguated ID Type / Status
Subject Minister-President of Württemberg E893957 entity
Predicate positionHeldBy P8 FINISHED
Object Karl von Weizsäcker
Karl von Weizsäcker was a German statesman and nobleman who served as a leading political figure in the Kingdom of Württemberg during the late 19th and early 20th centuries.
E2178546 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 von Weizsäcker | Statement: [Minister-President of Württemberg, positionHeldBy, Karl von Weizsäcker]
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 von Weizsäcker
Triple: [Minister-President of Württemberg, positionHeldBy, Karl von Weizsäcker]
Generated description
Karl von Weizsäcker was a German statesman and nobleman who served as a leading political figure in the Kingdom of Württemberg during the late 19th and early 20th centuries.

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_69f76e4c1b248190b10667d0213537fe completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7ba1f74e48190b7ba7aaafb644f63 completed May 3, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a397d867984819099f671196731feb4 completed June 22, 2026, 6:23 p.m.
NEDg Description generation batch_6a397f9cf3048190a6323f3031239176 completed June 22, 2026, 6:31 p.m.
NED2 Entity disambiguation (via description) batch_6a39835da5c48190a0cacb04de22724c completed June 22, 2026, 6:47 p.m.
Created at: May 3, 2026, 4:09 p.m.