Triple

T30321122
Position Surface form Disambiguated ID Type / Status
Subject Weihui E771201 entity
Predicate hasChineseName P4878 FINISHED
Object 卫辉市
卫辉市是位于中国河南省北部、隶属新乡市代管的一座县级城市,以历史悠久和濒临太行山、黄河冲积平原的地理位置而闻名。
E1911164 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: 卫辉市 | Statement: [Weihui, hasChineseName, 卫辉市]
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: 卫辉市
Triple: [Weihui, hasChineseName, 卫辉市]
Generated description
卫辉市是位于中国河南省北部、隶属新乡市代管的一座县级城市,以历史悠久和濒临太行山、黄河冲积平原的地理位置而闻名。

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_69f22489ee8481909344649bfbb92e83 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68197aac481909b701a91af7406e5 completed May 2, 2026, 10:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a277c1697988190931687a88b8ae11c completed June 9, 2026, 2:36 a.m.
NEDg Description generation batch_6a277db96e588190b880660e62bb2364 completed June 9, 2026, 2:43 a.m.
NED2 Entity disambiguation (via description) batch_6a277e55f0788190b9db58600d6de7d4 completed June 9, 2026, 2:45 a.m.
Created at: April 29, 2026, 7:52 p.m.