Triple

T38702415
Position Surface form Disambiguated ID Type / Status
Subject von Lichnowsky E950173 entity
Predicate hasAncestralSeat P2536 FINISHED
Object Lichnowsky estates in Silesia
The Lichnowsky estates in Silesia were the historic landed properties of the aristocratic von Lichnowsky family in the Silesian region of Central Europe.
E2281570 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: Lichnowsky estates in Silesia | Statement: [von Lichnowsky, hasAncestralSeat, Lichnowsky estates in Silesia]
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: Lichnowsky estates in Silesia
Triple: [von Lichnowsky, hasAncestralSeat, Lichnowsky estates in Silesia]
Generated description
The Lichnowsky estates in Silesia were the historic landed properties of the aristocratic von Lichnowsky family in the Silesian region of Central Europe.

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_69f76f0124408190bb39c3040734846b completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fcdc8c5ec48190b6aa759fcdf16354 completed May 7, 2026, 6:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4205cf5f0c81908a4f2e95c940385c completed June 29, 2026, 5:42 a.m.
NEDg Description generation batch_6a4207fdfa9c81908b46586b1204bd22 completed June 29, 2026, 5:51 a.m.
NED2 Entity disambiguation (via description) batch_6a42086985288190a3cf7b7f45859926 completed June 29, 2026, 5:53 a.m.
Created at: May 3, 2026, 4:33 p.m.