Triple

T31405699
Position Surface form Disambiguated ID Type / Status
Subject Marie-José Nat E801119 entity
Predicate notableWork P4 FINISHED
Object Les gens de Mogador
Les gens de Mogador is a French television drama series adapted from the novel by Élisabeth Barbier, chronicling the fortunes of a Provençal family over several generations.
E1960523 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: Les gens de Mogador | Statement: [Marie-José Nat, notableWork, Les gens de Mogador]
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: Les gens de Mogador
Triple: [Marie-José Nat, notableWork, Les gens de Mogador]
Generated description
Les gens de Mogador is a French television drama series adapted from the novel by Élisabeth Barbier, chronicling the fortunes of a Provençal family over several generations.

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_69f348c0dd648190bf2fd7642f78eb06 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a06052fc81908dc8b24574a43124 completed May 3, 2026, 1:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2ad2501a8881908aa7970d4d6c05f2 completed June 11, 2026, 3:20 p.m.
NEDg Description generation batch_6a2ad2dffa0c819094a5fe98e9f493dc completed June 11, 2026, 3:23 p.m.
NED2 Entity disambiguation (via description) batch_6a2ae095f2e4819092a90aa55fed57c4 completed June 11, 2026, 4:21 p.m.
Created at: April 30, 2026, 8:31 p.m.