Triple

T31916534
Position Surface form Disambiguated ID Type / Status
Subject Jacques Basnage E814844 entity
Predicate spouse P13 FINISHED
Object Suzanne Du Moulin
Suzanne Du Moulin was the wife of French Protestant pastor and historian Jacques Basnage, associated with the Huguenot intellectual and religious milieu of the late 17th and early 18th centuries.
E2029781 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: Suzanne Du Moulin | Statement: [Jacques Basnage, spouse, Suzanne Du Moulin]
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: Suzanne Du Moulin
Triple: [Jacques Basnage, spouse, Suzanne Du Moulin]
Generated description
Suzanne Du Moulin was the wife of French Protestant pastor and historian Jacques Basnage, associated with the Huguenot intellectual and religious milieu of the late 17th and early 18th centuries.

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_69f348f109d88190b5005372c53d2fcd completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b1ef9a84819092952e451b98987b completed May 3, 2026, 2:24 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34d23dafdc8190b846c2b970d76a0e completed June 19, 2026, 5:23 a.m.
NEDg Description generation batch_6a34d387ec3c81908afde8c0dbe2f700 completed June 19, 2026, 5:28 a.m.
NED2 Entity disambiguation (via description) batch_6a34d423fc108190aeb3f93fbabdf591 completed June 19, 2026, 5:31 a.m.
Created at: May 1, 2026, 12:02 a.m.