Triple
T12661110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yandang Mountains |
E302425
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
South Yandang
South Yandang is a scenic subregion of China’s Yandang Mountains known for its rugged peaks, waterfalls, and rich natural landscapes.
|
E302425
|
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: South Yandang | Statement: [Yandang Mountains, hasPart, South Yandang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: South Yandang Context triple: [Yandang Mountains, hasPart, South Yandang]
-
A.
Yandang Mountains
The Yandang Mountains are a renowned scenic mountain range in eastern China celebrated for their dramatic cliffs, waterfalls, and rich biodiversity.
-
B.
Yangsansi
Yangsansi is a city in South Korea located within Gyeonggi Province, forming part of the greater Seoul metropolitan area.
-
C.
Huanglong
Huanglong was a historical Chinese era name used during the reign of Eastern Wu ruler Sun Quan in the Three Kingdoms period.
-
D.
Gaotangling
Gaotangling is the town that serves as the administrative seat and political center of Wangcheng County in Hunan Province, China.
-
E.
Yufeng Mountain
Yufeng Mountain is a scenic, historically significant mountain and popular tourist destination located near Liuzhou in China’s Guangxi region.
- 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: South Yandang Triple: [Yandang Mountains, hasPart, South Yandang]
Generated description
South Yandang is a scenic subregion of China’s Yandang Mountains known for its rugged peaks, waterfalls, and rich natural landscapes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: South Yandang Target entity description: South Yandang is a scenic subregion of China’s Yandang Mountains known for its rugged peaks, waterfalls, and rich natural landscapes.
-
A.
Yandang Mountains
chosen
The Yandang Mountains are a renowned scenic mountain range in eastern China celebrated for their dramatic cliffs, waterfalls, and rich biodiversity.
-
B.
Yangsansi
Yangsansi is a city in South Korea located within Gyeonggi Province, forming part of the greater Seoul metropolitan area.
-
C.
Huanglong
Huanglong was a historical Chinese era name used during the reign of Eastern Wu ruler Sun Quan in the Three Kingdoms period.
-
D.
Gaotangling
Gaotangling is the town that serves as the administrative seat and political center of Wangcheng County in Hunan Province, China.
-
E.
Yufeng Mountain
Yufeng Mountain is a scenic, historically significant mountain and popular tourist destination located near Liuzhou in China’s Guangxi region.
- F. None of above.
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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9617b07ec8190b714f04ae6654060 |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f67c730b5c8190ae8dbb476e53729e |
completed | May 2, 2026, 10:36 p.m. |
| NEDg | Description generation | batch_69f67de172088190b055ace0fdcfd1fd |
completed | May 2, 2026, 10:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f67ececce8819080335e67bd747057 |
completed | May 2, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:19 p.m.