Triple

T27364070
Position Surface form Disambiguated ID Type / Status
Subject Hauberg Estate E685907 entity
Predicate namedAfter P63 FINISHED
Object Susanne Denkmann Hauberg
Susanne Denkmann Hauberg was a member of the prominent Denkmann family and a philanthropist whose legacy is commemorated by the historic Hauberg Estate that bears her name.
E1776119 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: Susanne Denkmann Hauberg | Statement: [Hauberg Estate, namedAfter, Susanne Denkmann Hauberg]
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: Susanne Denkmann Hauberg
Triple: [Hauberg Estate, namedAfter, Susanne Denkmann Hauberg]
Generated description
Susanne Denkmann Hauberg was a member of the prominent Denkmann family and a philanthropist whose legacy is commemorated by the historic Hauberg Estate that bears her name.

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_69ef14887c288190931b8431fdbf53c4 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f62c261bd0819096e201683858aa16 completed May 2, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12bbca05fc8190af7c7c243b23fee9 completed May 24, 2026, 8:50 a.m.
NEDg Description generation batch_6a12bd0d87a88190a617ee64551f7d93 completed May 24, 2026, 8:55 a.m.
NED2 Entity disambiguation (via description) batch_6a12be3a604c8190887660a427cd9f2f completed May 24, 2026, 9 a.m.
Created at: April 27, 2026, 11:55 a.m.