Triple

T31234283
Position Surface form Disambiguated ID Type / Status
Subject The Wild Child E796371 entity
Predicate hasCharacter P2308 FINISHED
Object Madame Guérin
Madame Guérin is a character in François Truffaut’s film *The Wild Child*, serving as a caretaker figure involved in the education and socialization of the feral boy Victor.
 E1959746 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: Madame Guérin | Statement: [The Wild Child, hasCharacter, Madame Guérin]
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: Madame Guérin
Triple: [The Wild Child, hasCharacter, Madame Guérin]
Generated description
Madame Guérin is a character in François Truffaut’s film *The Wild Child*, serving as a caretaker figure involved in the education and socialization of the feral boy Victor.

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_69f224db69ac81909a370adad6a7ac7c completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69d212650819088514cd8d7f141d9 completed May 3, 2026, 12:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2a71fb7f588190adf020c5d1e9b15a completed June 11, 2026, 8:29 a.m.
NEDg Description generation batch_6a2a75d68da48190b86388e077acf1e5 completed June 11, 2026, 8:46 a.m.
NED2 Entity disambiguation (via description) batch_6a2abcd99ec48190af20507cac16aae7 completed June 11, 2026, 1:49 p.m.
Created at: April 29, 2026, 9:10 p.m.