Triple

T27823480
Position Surface form Disambiguated ID Type / Status
Subject Hung E702883 entity
Predicate hasNotableBearer P458 FINISHED
Object Hung Chih-wei
Hung Chih-wei is a Taiwanese professional baseball player known for his career in the Chinese Professional Baseball League (CPBL).
E1820647 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: Hung Chih-wei | Statement: [Hung, hasNotableBearer, Hung Chih-wei]
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: Hung Chih-wei
Triple: [Hung, hasNotableBearer, Hung Chih-wei]
Generated description
Hung Chih-wei is a Taiwanese professional baseball player known for his career in the Chinese Professional Baseball League (CPBL).

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_69ef840ad1e88190b5bff2d1ddec8700 completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f6386fd3c881908bd96b538619cd0f completed May 2, 2026, 5:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a16415c1a1c8190b20d8a3e632c632b completed May 27, 2026, 12:57 a.m.
NEDg Description generation batch_6a164240e9308190aa46c9b0745446b7 completed May 27, 2026, 1 a.m.
NED2 Entity disambiguation (via description) batch_6a16467e0a3c8190aba09c9f0a65298c completed May 27, 2026, 1:18 a.m.
Created at: April 27, 2026, 5:50 p.m.