Triple
T17442844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 马鞍山 |
E424699
|
entity |
| Predicate | hasScenicArea |
P29946
|
FINISHED |
| Object |
雨山湖公园
雨山湖公园是位于安徽省马鞍山市的一座以湖景与休闲绿地为特色的城市公园与风景游览区。
|
E1269106
|
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: 雨山湖公园 | Statement: [马鞍山, hasScenicArea, 雨山湖公园]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 雨山湖公园 Context triple: [马鞍山, hasScenicArea, 雨山湖公园]
-
A.
北秀湖
北秀湖 is a scenic urban lake in China known for its landscaped surroundings and recreational waterfront environment.
-
B.
蛇山
蛇山 is a well-known hill in Wuhan, Hubei Province, China, noted for its scenic views over the Yangtze River and its historical and cultural significance.
-
C.
柳叶湖
柳叶湖是位于中国湖南省常德市、以优美湖景和休闲旅游资源闻名的淡水湖泊与风景名胜区。
-
D.
云龙山
云龙山是一座位于中国的山岳景区，以秀美的自然风光和人文景观而闻名。
-
E.
摩周湖
摩周湖は北海道東部の阿寒摩周国立公園内にある、世界有数の透明度を誇るカルデラ湖です。
- 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: 雨山湖公园 Triple: [马鞍山, hasScenicArea, 雨山湖公园]
Generated description
雨山湖公园是位于安徽省马鞍山市的一座以湖景与休闲绿地为特色的城市公园与风景游览区。
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 雨山湖公园 Target entity description: 雨山湖公园是位于安徽省马鞍山市的一座以湖景与休闲绿地为特色的城市公园与风景游览区。
-
A.
北秀湖
北秀湖 is a scenic urban lake in China known for its landscaped surroundings and recreational waterfront environment.
-
B.
蛇山
蛇山 is a well-known hill in Wuhan, Hubei Province, China, noted for its scenic views over the Yangtze River and its historical and cultural significance.
-
C.
柳叶湖
柳叶湖是位于中国湖南省常德市、以优美湖景和休闲旅游资源闻名的淡水湖泊与风景名胜区。
-
D.
云龙山
云龙山是一座位于中国的山岳景区，以秀美的自然风光和人文景观而闻名。
-
E.
摩周湖
摩周湖は北海道東部の阿寒摩周国立公園内にある、世界有数の透明度を誇るカルデラ湖です。
- 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_69d889db0ba481908402409af3b37917 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44ff927ec8190995798f569e913ba |
completed | April 19, 2026, 3:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01aff63d688190b8fa63c8edafc01c |
completed | May 11, 2026, 10:31 a.m. |
| NEDg | Description generation | batch_6a01b0a265348190a884a58f3caf54df |
completed | May 11, 2026, 10:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01b1b0553c8190bb76969fe95154ff |
completed | May 11, 2026, 10:38 a.m. |
Created at: April 10, 2026, 5:47 a.m.