Triple

T21766705
Position Surface form Disambiguated ID Type / Status
Subject Schlatter E537312 entity
Predicate hasNotableBearer P458 FINISHED
Object Francis Schlatter
Francis Schlatter was a late 19th-century mystic and faith healer in the United States who attracted widespread attention for his reputed miraculous cures and spiritual teachings.
E2193488 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: Francis Schlatter | Statement: [Schlatter, hasNotableBearer, Francis Schlatter]
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: Francis Schlatter
Triple: [Schlatter, hasNotableBearer, Francis Schlatter]
Generated description
Francis Schlatter was a late 19th-century mystic and faith healer in the United States who attracted widespread attention for his reputed miraculous cures and spiritual teachings.

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_69e0c46f5d1c8190bf830409e98464e5 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f031aa9c888190887c5c1d1e3bab9f completed April 28, 2026, 4:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3a20a5f92c8190a88be02dca401b78 completed June 23, 2026, 5:59 a.m.
NEDg Description generation batch_6a3a223909648190859223424fc876ef completed June 23, 2026, 6:05 a.m.
NED2 Entity disambiguation (via description) batch_6a3a22aa6b788190bed3fe999f1534ee completed June 23, 2026, 6:07 a.m.
Created at: April 16, 2026, 6:51 p.m.