Triple

T38646973
Position Surface form Disambiguated ID Type / Status
Subject Françoise Mouly E938744 entity
Predicate familyName P18 FINISHED
Object Mouly
Mouly is a French surname notably borne by Françoise Mouly, the influential art editor of The New Yorker and co-founder of the comics anthology RAW.
E2278798 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: Mouly | Statement: [Françoise Mouly, familyName, Mouly]
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: Mouly
Triple: [Françoise Mouly, familyName, Mouly]
Generated description
Mouly is a French surname notably borne by Françoise Mouly, the influential art editor of The New Yorker and co-founder of the comics anthology RAW.

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_69f76ed948ec81908ce7811608a8f359 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcd9db22588190984d73ac65661b70 completed May 7, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41f45ee08081908e3346ceda72a8ee completed June 29, 2026, 4:28 a.m.
NEDg Description generation batch_6a41f4e7480081908b9a4c8f6a7ee771 completed June 29, 2026, 4:30 a.m.
NED2 Entity disambiguation (via description) batch_6a41f5ee76048190b757881212799a4e completed June 29, 2026, 4:34 a.m.
Created at: May 3, 2026, 4:32 p.m.