Triple

T8968210
Position Surface form Disambiguated ID Type / Status
Subject Tsukada E214192 entity
Predicate hasNotableBearer P458 FINISHED
Object Tsukada Yūji
Tsukada Yūji is a Japanese individual notable enough to be specifically distinguished as a bearer of the surname Tsukada.
E2284972 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: Tsukada Yūji | Statement: [Tsukada, hasNotableBearer, Tsukada Yūji]
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: Tsukada Yūji
Triple: [Tsukada, hasNotableBearer, Tsukada Yūji]
Generated description
Tsukada Yūji is a Japanese individual notable enough to be specifically distinguished as a bearer of the surname Tsukada.

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_69ca839dbf608190a2f5990477115d29 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6764aca48190a5e472d1b6841886 completed April 1, 2026, 12:31 a.m.
NED1 Entity disambiguation (via context triple) batch_6a44ae87db848190aaeeb3e8b9bafaf1 completed July 1, 2026, 6:07 a.m.
NEDg Description generation batch_6a44af420a3c81908e745cf30829458f completed July 1, 2026, 6:10 a.m.
NED2 Entity disambiguation (via description) batch_6a44b0f6dd588190afdadab7cb60b2df completed July 1, 2026, 6:17 a.m.
Created at: March 30, 2026, 7:01 p.m.