Triple

T36941295
Position Surface form Disambiguated ID Type / Status
Subject Vincent Perez E913773 entity
Predicate directed P7373 FINISHED
Object The Secret (2007 film)
The Secret is a 2007 French supernatural drama film that explores themes of identity and family through a mysterious body-swapping incident between a mother and her teenage daughter.
E2204741 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: The Secret (2007 film) | Statement: [Vincent Perez, directed, The Secret (2007 film)]
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: The Secret (2007 film)
Triple: [Vincent Perez, directed, The Secret (2007 film)]
Generated description
The Secret is a 2007 French supernatural drama film that explores themes of identity and family through a mysterious body-swapping incident between a mother and her teenage daughter.

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_69f76e8a6a5c81909c1febf32bf3fe23 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f9fe1a1ca4819084c196f0041f0be2 completed May 5, 2026, 2:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e164344e08190931b37f6982d78ff completed June 26, 2026, 6:03 a.m.
NEDg Description generation batch_6a3e16c86a84819085a695e70971c83b completed June 26, 2026, 6:06 a.m.
NED2 Entity disambiguation (via description) batch_6a3e1de0bf6c819085b7d2ac2759776c completed June 26, 2026, 6:36 a.m.
Created at: May 3, 2026, 4:13 p.m.