Triple

T33484240
Position Surface form Disambiguated ID Type / Status
Subject Chengbei District E857565 entity
Predicate hasChineseName P4878 FINISHED
Object 城北区
城北区是中国青海省西宁市下辖的一个市辖区,以其位于市区北部的地理位置和城市功能区建设而闻名。
E2053429 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: 城北区 | Statement: [Chengbei District, hasChineseName, 城北区]
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: 城北区
Triple: [Chengbei District, hasChineseName, 城北区]
Generated description
城北区是中国青海省西宁市下辖的一个市辖区,以其位于市区北部的地理位置和城市功能区建设而闻名。

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_69f3497547608190a1a0f2365fb713ee completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e531be388190b1b4a0cb1bc1da75 completed May 3, 2026, 6:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3595b644f0819080864275f9490df5 completed June 19, 2026, 7:17 p.m.
NEDg Description generation batch_6a3599aae2e48190ac4967233e980b41 completed June 19, 2026, 7:34 p.m.
NED2 Entity disambiguation (via description) batch_6a359a3dd81081909104433137c7791f completed June 19, 2026, 7:36 p.m.
Created at: May 1, 2026, 1:38 a.m.