Triple

T31782841
Position Surface form Disambiguated ID Type / Status
Subject Wangjiang Campus E811249 entity
Predicate hasNameInChinese P4878 FINISHED
Object 望江校区
望江校区是位于中国四川省成都市、以人文与理工学科见长的四川大学主要校区之一。
E1978270 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: 望江校区 | Statement: [Wangjiang Campus, hasNameInChinese, 望江校区]
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: 望江校区
Triple: [Wangjiang Campus, hasNameInChinese, 望江校区]
Generated description
望江校区是位于中国四川省成都市、以人文与理工学科见长的四川大学主要校区之一。

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_69f348e544a48190ab6e700b05f6438c completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6abe67e20819093e9c1a8f6b39e37 completed May 3, 2026, 1:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2d9d5a94488190afa05e1b18512b86 completed June 13, 2026, 6:11 p.m.
NEDg Description generation batch_6a2d9e5cacf881909256095fa02d95a9 completed June 13, 2026, 6:15 p.m.
NED2 Entity disambiguation (via description) batch_6a2da22dea008190881a4e08691f9645 completed June 13, 2026, 6:32 p.m.
Created at: April 30, 2026, 11:36 p.m.