Triple

T29579253
Position Surface form Disambiguated ID Type / Status
Subject Louis de Funès E753528 entity
Predicate notableWork P4 FINISHED
Object Le Gendarme et les Extra-terrestres
Le Gendarme et les Extra-terrestres is a 1979 French comedy film in the popular "Gendarme" series, blending slapstick humor with a science-fiction plot about alien impostors in a small coastal town.
E1874064 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: Le Gendarme et les Extra-terrestres | Statement: [Louis de Funès, notableWork, Le Gendarme et les Extra-terrestres]
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: Le Gendarme et les Extra-terrestres
Triple: [Louis de Funès, notableWork, Le Gendarme et les Extra-terrestres]
Generated description
Le Gendarme et les Extra-terrestres is a 1979 French comedy film in the popular "Gendarme" series, blending slapstick humor with a science-fiction plot about alien impostors in a small coastal town.

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_69f0ef80bf8c8190ad286e99f7df0c63 completed April 28, 2026, 5:33 p.m.
NER Named-entity recognition batch_69f66d7825c08190953242afe9572940 completed May 2, 2026, 9:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a262d72afbc8190906c6ab972cb6d3c completed June 8, 2026, 2:48 a.m.
NEDg Description generation batch_6a2631635b348190a628533ebaab1a6b completed June 8, 2026, 3:05 a.m.
NED2 Entity disambiguation (via description) batch_6a26358d611c8190904db2b471839ee3 completed June 8, 2026, 3:22 a.m.
Created at: April 28, 2026, 6:05 p.m.