Triple

T28434183
Position Surface form Disambiguated ID Type / Status
Subject Northern Zhuang E715216 entity
Predicate hasDialect P4251 FINISHED
Object Youjiang Zhuang
Youjiang Zhuang is a regional variety of the Zhuang language spoken primarily in the Youjiang area of Guangxi, China.
E1821062 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: Youjiang Zhuang | Statement: [Northern Zhuang, hasDialect, Youjiang Zhuang]
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: Youjiang Zhuang
Triple: [Northern Zhuang, hasDialect, Youjiang Zhuang]
Generated description
Youjiang Zhuang is a regional variety of the Zhuang language spoken primarily in the Youjiang area of Guangxi, China.

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_69efd6b253888190b3c7222ed6a403a8 completed April 27, 2026, 9:35 p.m.
NER Named-entity recognition batch_69f64e37f7fc819083809149b6661e3c completed May 2, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a16417f7ab88190ad6a9ee75344b48a completed May 27, 2026, 12:57 a.m.
NEDg Description generation batch_6a1ca4ea5f9881909252686ff40ff9bd completed May 31, 2026, 9:15 p.m.
NED2 Entity disambiguation (via description) batch_6a1ca5e071008190a2014d179576fddb completed May 31, 2026, 9:19 p.m.
Created at: April 28, 2026, 1:41 a.m.