Triple

T17436021
Position Surface form Disambiguated ID Type / Status
Subject Seven Samurai E424003 entity
Predicate mainCharacter P1183 FINISHED
Object Katsushiro Okamoto
Katsushiro Okamoto is the young, idealistic samurai-in-training who joins the veteran warriors and matures through battle in Akira Kurosawa’s classic film "Seven Samurai."
E2286074 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: Katsushiro Okamoto | Statement: [Seven Samurai, mainCharacter, Katsushiro Okamoto]
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: Katsushiro Okamoto
Triple: [Seven Samurai, mainCharacter, Katsushiro Okamoto]
Generated description
Katsushiro Okamoto is the young, idealistic samurai-in-training who joins the veteran warriors and matures through battle in Akira Kurosawa’s classic film "Seven Samurai."

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_69d889d88b6081908bada047f5b3ba51 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4490426008190b474ed76aca5d6f3 completed April 19, 2026, 3:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a464b0ba2248190b88a253f6da98b27 completed July 2, 2026, 11:27 a.m.
NEDg Description generation batch_6a464bc92d8c81908e6a0ad938840123 completed July 2, 2026, 11:30 a.m.
NED2 Entity disambiguation (via description) batch_6a464c3d5e748190beae969583298369 completed July 2, 2026, 11:32 a.m.
Created at: April 10, 2026, 5:46 a.m.