Triple

T34052377
Position Surface form Disambiguated ID Type / Status
Subject Kenichi E873257 entity
Predicate canBeWrittenWithKanji P59069 FINISHED
Object 健一
健一 is a common Japanese male given name typically conveying meanings related to health or strength combined with the notion of being first or number one.
E2079606 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: 健一 | Statement: [Kenichi, canBeWrittenWithKanji, 健一]
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: 健一
Triple: [Kenichi, canBeWrittenWithKanji, 健一]
Generated description
健一 is a common Japanese male given name typically conveying meanings related to health or strength combined with the notion of being first or number one.

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_69f349a3ec2c8190b62da76e54231a0f completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70b68f25481909d31021dad76021e completed May 3, 2026, 8:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36a0408a308190b1cc78df488cecc5 completed June 20, 2026, 2:14 p.m.
NEDg Description generation batch_6a36a0df14288190a9b82728daac1f69 completed June 20, 2026, 2:17 p.m.
NED2 Entity disambiguation (via description) batch_6a36a16a05a48190aac973a431bb7cc7 completed June 20, 2026, 2:19 p.m.
Created at: May 1, 2026, 1:52 a.m.