Triple

T30242742
Position Surface form Disambiguated ID Type / Status
Subject The Naked Kiss E768961 entity
Predicate includedIn P1393 FINISHED
Object Samuel Fuller filmography
Samuel Fuller filmography is the complete list of films written and/or directed by the American filmmaker Samuel Fuller, known for his hard-boiled, socially charged genre movies.
E1906172 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: Samuel Fuller filmography | Statement: [The Naked Kiss, includedIn, Samuel Fuller filmography]
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: Samuel Fuller filmography
Triple: [The Naked Kiss, includedIn, Samuel Fuller filmography]
Generated description
Samuel Fuller filmography is the complete list of films written and/or directed by the American filmmaker Samuel Fuller, known for his hard-boiled, socially charged genre movies.

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_69f224820c048190b1435c4cc145acf1 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6805072f88190a05c0467cdeffb8a completed May 2, 2026, 10:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27644ff7908190aca2fa3b789ed231 completed June 9, 2026, 12:54 a.m.
NEDg Description generation batch_6a2766016dd08190895ed5102bf1532a completed June 9, 2026, 1:01 a.m.
NED2 Entity disambiguation (via description) batch_6a2766e3b5bc81908ae6c55770c85a3d completed June 9, 2026, 1:05 a.m.
Created at: April 29, 2026, 7:39 p.m.