Triple

T9731880
Position Surface form Disambiguated ID Type / Status
Subject Xialu District E235763 entity
Predicate hasChineseName P4878 FINISHED
Object 下陆区
下陆区 is an urban district of Huangshi City in Hubei Province, China, known for its industrial base and role in the city’s economic development.
E816304 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: 下陆区 | Statement: [Xialu District, hasChineseName, 下陆区]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 下陆区
Context triple: [Xialu District, hasChineseName, 下陆区]
  • A. 黄石港区
    黄石港区 is an urban district of Huangshi City in Hubei Province, China, known as one of the city’s central administrative and commercial areas along the Yangtze River.
  • B. 大冶市
    大冶市 is a county-level city in southeastern Hubei Province, China, known historically for its rich mineral resources and metal smelting industry.
  • C. 张湾区
    张湾区是湖北省十堰市下辖的一个市辖区和主要城区之一,以工业基础和城市综合功能较为发达而著称。
  • D. 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。
  • E. Jianghan District
    Jianghan District is a central urban district of Wuhan, Hubei Province, known for its commercial hubs and historical and cultural sites.
  • 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: 下陆区
Triple: [Xialu District, hasChineseName, 下陆区]
Generated description
下陆区 is an urban district of Huangshi City in Hubei Province, China, known for its industrial base and role in the city’s economic development.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 下陆区
Target entity description: 下陆区 is an urban district of Huangshi City in Hubei Province, China, known for its industrial base and role in the city’s economic development.
  • A. 黄石港区
    黄石港区 is an urban district of Huangshi City in Hubei Province, China, known as one of the city’s central administrative and commercial areas along the Yangtze River.
  • B. 大冶市
    大冶市 is a county-level city in southeastern Hubei Province, China, known historically for its rich mineral resources and metal smelting industry.
  • C. 张湾区
    张湾区是湖北省十堰市下辖的一个市辖区和主要城区之一,以工业基础和城市综合功能较为发达而著称。
  • D. 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。
  • E. Jianghan District
    Jianghan District is a central urban district of Wuhan, Hubei Province, known for its commercial hubs and historical and cultural sites.
  • 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_69ca84d0fad481909cdd45aa77416c48 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9eb3d6e4819090b3c7fb92550c57 completed April 1, 2026, 10:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69d19fbbba2081909a15725a68423162 completed April 4, 2026, 11:33 p.m.
NEDg Description generation batch_69d1a065ce008190985b792302daa7cb completed April 4, 2026, 11:36 p.m.
NED2 Entity disambiguation (via description) batch_69d1a0f811fc8190b6a46a0441159089 completed April 4, 2026, 11:38 p.m.
Created at: March 30, 2026, 8:22 p.m.