Triple
T3696918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hanyang District |
E78480
|
entity |
| Predicate | hasChineseName |
P4878
|
FINISHED |
| Object | 汉阳区 |
E99504
|
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: 汉阳区 | Statement: [Hanyang District, hasChineseName, 汉阳区]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 汉阳区 Context triple: [Hanyang District, hasChineseName, 汉阳区]
-
A.
汉阳
chosen
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.
Jianghan District
Jianghan District is a central urban district of Wuhan, Hubei Province, known for its commercial hubs and historical and cultural sites.
-
C.
Jiang’an District, Wuhan
Jiang’an District is a central urban district of Wuhan, China, known for its historic riverfront along the Yangtze and Han rivers and its legacy as part of the former foreign concession area in Hankou.
-
D.
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。
-
E.
Wuchang District
Wuchang District is a central urban district of Wuhan, China, known for its historical significance, educational institutions, and location along the Yangtze River.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ad85e3b1888190abc983e06968696d |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc5115ad8819085ffa938de3943f4 |
completed | March 8, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4c3d4821081909ccd1b5789eb761e |
completed | March 14, 2026, 2:11 a.m. |
Created at: March 8, 2026, 3:26 p.m.