Triple
T8053005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xinyu |
E187720
|
entity |
| Predicate | hasCitySeat |
P15001
|
FINISHED |
| Object |
Yushui District
Yushui District is the central urban district and administrative seat of Xinyu, a prefecture-level city in Jiangxi Province, China.
|
E727253
|
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: Yushui District | Statement: [Xinyu, hasCitySeat, Yushui District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yushui District Context triple: [Xinyu, hasCitySeat, Yushui District]
-
A.
Yuhua District
Yuhua District is an urban administrative district of Changsha, the capital city of Hunan Province in south-central China.
-
B.
Mawei District
Mawei District is an urban district of Fuzhou in Fujian Province, China, historically known as a key shipbuilding and maritime center.
-
C.
Yunxi District
Yunxi District is an urban administrative district of Yueyang City in Hunan Province, China, known for its location along the Yangtze River and Dongting Lake region.
-
D.
Xialu District
Xialu District is an urban administrative district of the prefecture-level city of Huangshi in Hubei Province, China.
-
E.
Zhifu District
Zhifu District is the central urban district and administrative, commercial, and cultural core of Yantai in Shandong Province, China.
- 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: Yushui District Triple: [Xinyu, hasCitySeat, Yushui District]
Generated description
Yushui District is the central urban district and administrative seat of Xinyu, a prefecture-level city in Jiangxi Province, China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yushui District Target entity description: Yushui District is the central urban district and administrative seat of Xinyu, a prefecture-level city in Jiangxi Province, China.
-
A.
Yuhua District
Yuhua District is an urban administrative district of Changsha, the capital city of Hunan Province in south-central China.
-
B.
Mawei District
Mawei District is an urban district of Fuzhou in Fujian Province, China, historically known as a key shipbuilding and maritime center.
-
C.
Yunxi District
Yunxi District is an urban administrative district of Yueyang City in Hunan Province, China, known for its location along the Yangtze River and Dongting Lake region.
-
D.
Xialu District
Xialu District is an urban administrative district of the prefecture-level city of Huangshi in Hubei Province, China.
-
E.
Zhifu District
Zhifu District is the central urban district and administrative, commercial, and cultural core of Yantai in Shandong Province, China.
- 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_69ca82b15e948190a62fd7af5218426a |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3f7c425c8190aa1b2f534afeb58c |
completed | March 31, 2026, 3:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cdc64982d08190976144beafcd231d |
completed | April 2, 2026, 1:28 a.m. |
| NEDg | Description generation | batch_69cdcb8cbd3c8190b467ecbcf55231e9 |
completed | April 2, 2026, 1:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cdccff097c819099a33612504468e1 |
completed | April 2, 2026, 1:57 a.m. |
Created at: March 30, 2026, 5:25 p.m.