Triple

T31272926
Position Surface form Disambiguated ID Type / Status
Subject Ordrupgaard Museum E797436 entity
Predicate namedAfter P63 FINISHED
Object Ordrupgaard estate
Ordrupgaard estate is a historic Danish country property north of Copenhagen that became renowned as the site and namesake of the Ordrupgaard art museum and its notable art collection.
E797436 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: Ordrupgaard estate | Statement: [Ordrupgaard Museum, namedAfter, Ordrupgaard estate]
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: Ordrupgaard estate
Triple: [Ordrupgaard Museum, namedAfter, Ordrupgaard estate]
Generated description
Ordrupgaard estate is a historic Danish country property north of Copenhagen that became renowned as the site and namesake of the Ordrupgaard art museum and its notable art collection.

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_69f224de2bbc819081af6c32e1d857b9 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69dcf54e08190a666db62c27145c9 completed May 3, 2026, 12:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a296c050a4c81909023b1c0bc4ca460 completed June 10, 2026, 1:52 p.m.
NEDg Description generation batch_6a297030ba3481909ffb0a9664b27919 completed June 10, 2026, 2:09 p.m.
NED2 Entity disambiguation (via description) batch_6a29a767f82c8190a66ce069aaa3e6bf completed June 10, 2026, 6:05 p.m.
Created at: April 29, 2026, 9:13 p.m.