Triple
T14720781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Hong |
E345806
|
entity |
| Predicate | hasNameInChinese |
P4878
|
FINISHED |
| Object |
洪山
洪山 is a notable mountain in China known for its cultural and natural significance.
|
E1115560
|
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: 洪山 | Statement: [Mount Hong, hasNameInChinese, 洪山]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 洪山 Context triple: [Mount Hong, hasNameInChinese, 洪山]
-
A.
黄陂
黄陂是中国湖北省武汉市下辖的一个区，位于长江中游北岸，以其悠久历史和城乡结合的区域特征而闻名。
-
B.
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。
-
C.
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.
-
D.
青山
青山は、東京都港区と渋谷区にまたがる洗練された商業エリアで、高級ブティックやカフェ、ギャラリーが集まるおしゃれな街として知られています。
-
E.
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。
- 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: 洪山 Triple: [Mount Hong, hasNameInChinese, 洪山]
Generated description
洪山 is a notable mountain in China known for its cultural and natural significance.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 洪山 Target entity description: 洪山 is a notable mountain in China known for its cultural and natural significance.
-
A.
黄陂
黄陂是中国湖北省武汉市下辖的一个区，位于长江中游北岸，以其悠久历史和城乡结合的区域特征而闻名。
-
B.
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。
-
C.
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.
-
D.
青山
青山は、東京都港区と渋谷区にまたがる洗練された商業エリアで、高級ブティックやカフェ、ギャラリーが集まるおしゃれな街として知られています。
-
E.
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。
- 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_69d822e5911c8190ba589f957dbd9ba7 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec25d56fc8190871873ca55d49272 |
completed | April 14, 2026, 10:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdf0957bb081908f1f382f3be8ec20 |
completed | May 8, 2026, 2:17 p.m. |
| NEDg | Description generation | batch_69fdf440a03c8190886119ab3c8ab610 |
completed | May 8, 2026, 2:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fdf4f2acbc8190b51ee456093a2813 |
completed | May 8, 2026, 2:36 p.m. |
Created at: April 10, 2026, 1:29 a.m.