Triple

T36990910
Position Surface form Disambiguated ID Type / Status
Subject Johann Anton Leisewitz E915093 entity
Predicate spouse P13 FINISHED
Object Sophie Marie Katharina Seyler
Sophie Marie Katharina Seyler was an 18th-century German actress and member of the prominent Seyler theatrical family, active in the flourishing German theater scene of her time.
E2209362 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: Sophie Marie Katharina Seyler | Statement: [Johann Anton Leisewitz, spouse, Sophie Marie Katharina Seyler]
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: Sophie Marie Katharina Seyler
Triple: [Johann Anton Leisewitz, spouse, Sophie Marie Katharina Seyler]
Generated description
Sophie Marie Katharina Seyler was an 18th-century German actress and member of the prominent Seyler theatrical family, active in the flourishing German theater scene of her time.

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_69f76e8dd0408190b8b46da118ea5128 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f9ffdc413c8190a1197d2fc5f1f633 completed May 5, 2026, 2:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e575e17e881908caff179fe05f990 completed June 26, 2026, 10:41 a.m.
NEDg Description generation batch_6a3e57c7955c8190a5599baf3b52ad3b completed June 26, 2026, 10:43 a.m.
NED2 Entity disambiguation (via description) batch_6a3e827040dc8190a772d787b82133ab completed June 26, 2026, 1:45 p.m.
Created at: May 3, 2026, 4:14 p.m.