Triple

T14519865
Position Surface form Disambiguated ID Type / Status
Subject A Fistful of Dollars E340622 entity
Predicate basedOnWorkBy P2806 FINISHED
Object Ryūzō Kikushima
Ryūzō Kikushima was a Japanese screenwriter and frequent Akira Kurosawa collaborator, known for co-writing influential samurai films that inspired later Westerns.
E1763116 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: Ryūzō Kikushima | Statement: [A Fistful of Dollars, basedOnWorkBy, Ryūzō Kikushima]
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: Ryūzō Kikushima
Triple: [A Fistful of Dollars, basedOnWorkBy, Ryūzō Kikushima]
Generated description
Ryūzō Kikushima was a Japanese screenwriter and frequent Akira Kurosawa collaborator, known for co-writing influential samurai films that inspired later Westerns.

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_69d822d9c0408190b9a2b3643e58bb4d completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69de9a70b15c81908773633e989ef704 completed April 14, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a126239807881908843eaced3181240 completed May 24, 2026, 2:28 a.m.
NEDg Description generation batch_6a12667d95ec8190900555e50d903e5d completed May 24, 2026, 2:46 a.m.
NED2 Entity disambiguation (via description) batch_6a1266dd3b748190a06a76a7587eff99 completed May 24, 2026, 2:47 a.m.
Created at: April 10, 2026, 1:22 a.m.