Triple

T35440348
Position Surface form Disambiguated ID Type / Status
Subject The Scent of Green Papaya E1024323 entity
Predicate producer P490 FINISHED
Object Alain Rocca
Alain Rocca is a French film producer best known for his work on acclaimed art-house and international films, including the Oscar-nominated "The Scent of Green Papaya."
E2294763 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: Alain Rocca | Statement: [The Scent of Green Papaya, producer, Alain Rocca]
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: Alain Rocca
Triple: [The Scent of Green Papaya, producer, Alain Rocca]
Generated description
Alain Rocca is a French film producer best known for his work on acclaimed art-house and international films, including the Oscar-nominated "The Scent of Green Papaya."

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_69f76df8089481909f0018266ee881b7 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f795c200f48190a596f34fdae23fd7 completed May 3, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7c1a6222408190938077f31b2c3294 completed Aug. 12, 2026, 7:01 a.m.
NEDg Description generation batch_6a7c1ac0c2bc8190b33eb167cb4d70c6 completed Aug. 12, 2026, 7:03 a.m.
NED2 Entity disambiguation (via description) batch_6a7c1af4bc9c8190af628e5180b570bf completed Aug. 12, 2026, 7:04 a.m.
Created at: May 3, 2026, 4:04 p.m.