Triple

T1851136
Position Surface form Disambiguated ID Type / Status
Subject Huanggang E41595 entity
Predicate hasChineseName P4878 FINISHED
Object 黄冈市
黄冈市是中国湖北省东部的一座地级市,位于长江中游、与武汉相邻,以其红色革命历史和丰富的自然资源而闻名。
E204941 NE FINISHED

How this triple was built (4 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: 黄冈市 | Statement: [Huanggang, hasChineseName, 黄冈市]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 黄冈市
Context triple: [Huanggang, hasChineseName, 黄冈市]
  • A. 汉阳
    汉阳是中国湖北省武汉市的一个历史悠久的城区,位于长江与汉江交汇处,以其工业基础和文化遗产而闻名。
  • B. Huangshi Municipal People's Government
    Huangshi Municipal People's Government is the principal administrative authority responsible for local governance, public services, and policy implementation in the prefecture-level city of Huangshi, Hubei Province, China.
  • C. Suizhou
    Suizhou is a county-level city in northern Hubei Province, China, known for its historical sites and role as a regional transport and economic hub.
  • D. 十堰
    十堰 is a prefecture-level city in northwestern Hubei Province, China, known as an important automotive manufacturing base and gateway to the Wudang Mountains.
  • E. Xiaogan
    Xiaogan is a prefecture-level city in central China known for its cultural heritage and proximity to the provincial capital, Wuhan, within Hubei Province.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: 黄冈市
Triple: [Huanggang, hasChineseName, 黄冈市]
Generated description
黄冈市是中国湖北省东部的一座地级市,位于长江中游、与武汉相邻,以其红色革命历史和丰富的自然资源而闻名。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 黄冈市
Target entity description: 黄冈市是中国湖北省东部的一座地级市,位于长江中游、与武汉相邻,以其红色革命历史和丰富的自然资源而闻名。
  • A. 汉阳
    汉阳是中国湖北省武汉市的一个历史悠久的城区,位于长江与汉江交汇处,以其工业基础和文化遗产而闻名。
  • B. Huangshi Municipal People's Government
    Huangshi Municipal People's Government is the principal administrative authority responsible for local governance, public services, and policy implementation in the prefecture-level city of Huangshi, Hubei Province, China.
  • C. Suizhou
    Suizhou is a county-level city in northern Hubei Province, China, known for its historical sites and role as a regional transport and economic hub.
  • D. 十堰
    十堰 is a prefecture-level city in northwestern Hubei Province, China, known as an important automotive manufacturing base and gateway to the Wudang Mountains.
  • E. Xiaogan
    Xiaogan is a prefecture-level city in central China known for its cultural heritage and proximity to the provincial capital, Wuhan, within Hubei Province.
  • F. None of above. chosen

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_69a8864a83848190a4ec02721306c511 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb06829b081908767b3df5524c7d4 completed March 7, 2026, 4:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69adc9c81f2c81908339f6a1d1987631 completed March 8, 2026, 7:11 p.m.
NEDg Description generation batch_69adcb1565a881908dfc906654429e3f completed March 8, 2026, 7:16 p.m.
NED2 Entity disambiguation (via description) batch_69adcbbc8a108190ad77e91f2ec14b8f completed March 8, 2026, 7:19 p.m.
Created at: March 4, 2026, 7:33 p.m.