Triple

T35399310
Position Surface form Disambiguated ID Type / Status
Subject Max and the Junkmen E1023175 entity
Predicate hasAlternativeTitle P39 FINISHED
Object Max et les ferrailleurs
Max et les ferrailleurs is a 1971 French crime drama film directed by Claude Sautet, following a methodical police inspector who manipulates a gang of small-time crooks into committing a bank robbery so he can catch them in the act.
E2138939 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: Max et les ferrailleurs | Statement: [Max and the Junkmen, hasAlternativeTitle, Max et les ferrailleurs]
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: Max et les ferrailleurs
Triple: [Max and the Junkmen, hasAlternativeTitle, Max et les ferrailleurs]
Generated description
Max et les ferrailleurs is a 1971 French crime drama film directed by Claude Sautet, following a methodical police inspector who manipulates a gang of small-time crooks into committing a bank robbery so he can catch them in the act.

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_69f76df43ca4819098711ca4370f1bb9 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f795392adc8190becbe6ab9fd432ca completed May 3, 2026, 6:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a382ccae0c8819084cd76754161c605 completed June 21, 2026, 6:26 p.m.
NEDg Description generation batch_6a382d5989bc8190965463f119c6679e completed June 21, 2026, 6:28 p.m.
NED2 Entity disambiguation (via description) batch_6a382e1f37188190ac188d12cc6dce07 completed June 21, 2026, 6:31 p.m.
Created at: May 3, 2026, 4:03 p.m.