Triple

T36702445
Position Surface form Disambiguated ID Type / Status
Subject Louise Thaden E906265 entity
Predicate spouse P13 FINISHED
Object Herbert von Thaden
Herbert von Thaden was an American furniture and industrial designer known for pioneering molded plywood and modernist designs in the early 20th century.
 E2240686 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: Herbert von Thaden | Statement: [Louise Thaden, spouse, Herbert von Thaden]
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: Herbert von Thaden
Triple: [Louise Thaden, spouse, Herbert von Thaden]
Generated description
Herbert von Thaden was an American furniture and industrial designer known for pioneering molded plywood and modernist designs in the early 20th century.

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_69f76e7195c48190b5580c9cfb01e95f completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c7ee28c88190ad3f7adabd4650fc completed May 3, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40d65aaf84819081134e193d1317b3 completed June 28, 2026, 8:07 a.m.
NEDg Description generation batch_6a40d972cb848190bb94bb02a02e1e8a completed June 28, 2026, 8:21 a.m.
NED2 Entity disambiguation (via description) batch_6a40d9c9bf4c8190b7551c44c6f1a6ff completed June 28, 2026, 8:22 a.m.
Created at: May 3, 2026, 4:12 p.m.