Triple
T11207016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jiujiang |
E265194
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Lianxi District
Lianxi District is an urban administrative district of Jiujiang City in Jiangxi Province, China.
|
E930334
|
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: Lianxi District | Statement: [Jiujiang, hasSubdivision, Lianxi District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lianxi District Context triple: [Jiujiang, hasSubdivision, Lianxi District]
-
A.
Linwei District
Linwei District is an urban administrative district in Weinan, Shaanxi Province, China, serving as the city's central political and economic area.
-
B.
Zhifu District
Zhifu District is the central urban district and administrative, commercial, and cultural core of Yantai in Shandong Province, China.
-
C.
Shuangxi District
Shuangxi District is a rural, mountainous district in eastern New Taipei City, Taiwan, known for its rivers, old streets, and natural scenery.
-
D.
Lianyun District
Lianyun District is an urban coastal district of Lianyungang in Jiangsu Province, China, known for its port facilities and seaside location on the Yellow Sea.
-
E.
Zhanyi District
Zhanyi District is an administrative district under the jurisdiction of Qujing City in Yunnan Province, China, known for its role in regional agriculture and transportation.
- 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: Lianxi District Triple: [Jiujiang, hasSubdivision, Lianxi District]
Generated description
Lianxi District is an urban administrative district of Jiujiang City in Jiangxi Province, China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lianxi District Target entity description: Lianxi District is an urban administrative district of Jiujiang City in Jiangxi Province, China.
-
A.
Linwei District
Linwei District is an urban administrative district in Weinan, Shaanxi Province, China, serving as the city's central political and economic area.
-
B.
Zhifu District
Zhifu District is the central urban district and administrative, commercial, and cultural core of Yantai in Shandong Province, China.
-
C.
Shuangxi District
Shuangxi District is a rural, mountainous district in eastern New Taipei City, Taiwan, known for its rivers, old streets, and natural scenery.
-
D.
Lianyun District
Lianyun District is an urban coastal district of Lianyungang in Jiangsu Province, China, known for its port facilities and seaside location on the Yellow Sea.
-
E.
Zhanyi District
Zhanyi District is an administrative district under the jurisdiction of Qujing City in Yunnan Province, China, known for its role in regional agriculture and transportation.
- 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_69d6aac59460819089b9848b27f57848 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8d4eef88190a7f05bca82d919b9 |
completed | April 9, 2026, 5:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e623e44c188190b5b83cf8f397554c |
completed | April 20, 2026, 1:02 p.m. |
| NEDg | Description generation | batch_69e62aee8fb88190b5973c61e692087f |
completed | April 20, 2026, 1:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e67394e7f081908fcc602c84eb4a65 |
completed | April 20, 2026, 6:42 p.m. |
Created at: April 8, 2026, 9:30 p.m.