Triple

T25835014
Position Surface form Disambiguated ID Type / Status
Subject Lockwood–Mathews Mansion Museum E650770 entity
Predicate architect P184 FINISHED
Object Detlef Lienau
Detlef Lienau was a 19th-century German-American architect known for introducing European styles to the United States and designing prominent Gilded Age residences.
E2286726 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: Detlef Lienau | Statement: [Lockwood–Mathews Mansion Museum, architect, Detlef Lienau]
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: Detlef Lienau
Triple: [Lockwood–Mathews Mansion Museum, architect, Detlef Lienau]
Generated description
Detlef Lienau was a 19th-century German-American architect known for introducing European styles to the United States and designing prominent Gilded Age residences.

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_69e7ab37438081908f1ccf6284839520 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f601f485c48190bdbeb260653d9849 completed May 2, 2026, 1:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a46dad2bea08190a43d17a71ee0c7d8 completed July 2, 2026, 9:40 p.m.
NEDg Description generation batch_6a46dbac01f48190bba3032c30daf73f completed July 2, 2026, 9:44 p.m.
NED2 Entity disambiguation (via description) batch_6a46f3b413ac819080a7216c7f187060 completed July 2, 2026, 11:26 p.m.
Created at: April 22, 2026, 7:41 a.m.