Triple

T31818064
Position Surface form Disambiguated ID Type / Status
Subject Samuel Yin E812190 entity
Predicate nativeName P15 FINISHED
Object 尹衍樑
尹衍樑 is a prominent Taiwanese billionaire businessman and philanthropist, best known as the chairman of the Ruentex Group and founder of the Tang Prize.
E1977091 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: 尹衍樑 | Statement: [Samuel Yin, nativeName, 尹衍樑]
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: 尹衍樑
Triple: [Samuel Yin, nativeName, 尹衍樑]
Generated description
尹衍樑 is a prominent Taiwanese billionaire businessman and philanthropist, best known as the chairman of the Ruentex Group and founder of the Tang Prize.

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_69f348e846c081908eb468a0665afd55 completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6ad069568819098fe0fcb135641fc completed May 3, 2026, 2:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2d9d7372ec8190ad9419feb4512d8d completed June 13, 2026, 6:12 p.m.
NEDg Description generation batch_6a2d9e6d021481908201446811a134ef completed June 13, 2026, 6:16 p.m.
NED2 Entity disambiguation (via description) batch_6a2d9f0a0cf08190b4787d259334a31e completed June 13, 2026, 6:18 p.m.
Created at: April 30, 2026, 11:45 p.m.