Triple

T9806867
Position Surface form Disambiguated ID Type / Status
Subject Chugai Pharmaceutical E238175 entity
Predicate foundedBy P104 FINISHED
Object Juzo Ueno
Juzo Ueno was a Japanese entrepreneur best known as the founder of the major pharmaceutical company Chugai Pharmaceutical.
E2296819 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: Juzo Ueno | Statement: [Chugai Pharmaceutical, foundedBy, Juzo Ueno]
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: Juzo Ueno
Triple: [Chugai Pharmaceutical, foundedBy, Juzo Ueno]
Generated description
Juzo Ueno was a Japanese entrepreneur best known as the founder of the major pharmaceutical company Chugai Pharmaceutical.

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_69ca84defac48190abc1148804f184c1 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdab7cb9588190953a063cb7b9e29e completed April 1, 2026, 11:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a82be57ba188190bd36834ed459e161 completed Aug. 17, 2026, 7:55 a.m.
NEDg Description generation batch_6a82bec28d7081909d86dcde047c9102 completed Aug. 17, 2026, 7:56 a.m.
NED2 Entity disambiguation (via description) batch_6a82bf388bd08190afe213cb9dc75da4 completed Aug. 17, 2026, 7:58 a.m.
Created at: March 30, 2026, 8:29 p.m.