Triple

T35791825
Position Surface form Disambiguated ID Type / Status
Subject Until the End of the World E1034711 entity
Predicate producer P490 FINISHED
Object Bertrand Faivre
Bertrand Faivre is a film producer known for his work on international and independent cinema, including projects like Wim Wenders' "Until the End of the World."
E2295110 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: Bertrand Faivre | Statement: [Until the End of the World, producer, Bertrand Faivre]
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: Bertrand Faivre
Triple: [Until the End of the World, producer, Bertrand Faivre]
Generated description
Bertrand Faivre is a film producer known for his work on international and independent cinema, including projects like Wim Wenders' "Until the End of the World."

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_69f76e1575908190aaa306d843b41c14 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a22f2e9881908ed7de25b791813a completed May 3, 2026, 7:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7d067e7bf881909a35a6752d7c71ec completed Aug. 12, 2026, 11:49 p.m.
NEDg Description generation batch_6a7d06ec01fc8190bb59ff1e8560a74e completed Aug. 12, 2026, 11:51 p.m.
NED2 Entity disambiguation (via description) batch_6a7d0976933481908c7e6bf4ec58d382 completed Aug. 13, 2026, 12:01 a.m.
Created at: May 3, 2026, 4:06 p.m.