Triple
T14099463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jiulongshan |
E339341
|
entity |
| Predicate | ChineseName |
P744
|
FINISHED |
| Object |
九龙山站
九龙山站是位于中国北京地铁亦庄线与7号线换乘处的一座城市轨道交通车站。
|
E1079974
|
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: 九龙山站 | Statement: [Jiulongshan, ChineseName, 九龙山站]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 九龙山站 Context triple: [Jiulongshan, ChineseName, 九龙山站]
-
A.
Kengkou station
Kengkou station is a metro station on the Guangzhou Metro network in Guangzhou, China.
-
B.
Baishizhou station
Baishizhou station is a metro station in Shenzhen, China, serving the densely populated Baishizhou area and nearby attractions such as Window of the World.
-
C.
Zhichunlu station
Zhichunlu station is a subway station in Beijing that serves as part of the city's extensive urban rail transit network.
-
D.
Kunshan South railway station
Kunshan South railway station is a major high-speed rail hub in Kunshan, Jiangsu Province, serving as an important stop on the Shanghai–Nanjing intercity railway.
-
E.
Beitucheng station
Beitucheng station is an interchange station on the Beijing Subway that connects Line 8 with other key routes in the city's metro network.
- 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: 九龙山站 Triple: [Jiulongshan, ChineseName, 九龙山站]
Generated description
九龙山站是位于中国北京地铁亦庄线与7号线换乘处的一座城市轨道交通车站。
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 九龙山站 Target entity description: 九龙山站是位于中国北京地铁亦庄线与7号线换乘处的一座城市轨道交通车站。
-
A.
Kengkou station
Kengkou station is a metro station on the Guangzhou Metro network in Guangzhou, China.
-
B.
Baishizhou station
Baishizhou station is a metro station in Shenzhen, China, serving the densely populated Baishizhou area and nearby attractions such as Window of the World.
-
C.
Zhichunlu station
Zhichunlu station is a subway station in Beijing that serves as part of the city's extensive urban rail transit network.
-
D.
Kunshan South railway station
Kunshan South railway station is a major high-speed rail hub in Kunshan, Jiangsu Province, serving as an important stop on the Shanghai–Nanjing intercity railway.
-
E.
Beitucheng station
Beitucheng station is an interchange station on the Beijing Subway that connects Line 8 with other key routes in the city's metro network.
- 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_69d81c69b5c8819094aa1abf18302908 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5fba7c10819095b1299b7b4f0310 |
completed | April 14, 2026, 3:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcd0adfc28819097a1bfd56739c286 |
completed | May 7, 2026, 5:49 p.m. |
| NEDg | Description generation | batch_69fcd41c84408190ab4bc885e7ba8f81 |
completed | May 7, 2026, 6:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fcd4ab4b588190977b3dc2adc1f412 |
completed | May 7, 2026, 6:06 p.m. |
Created at: April 9, 2026, 10:22 p.m.