Triple
T16124224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamsui–Xinyi line |
E391223
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Zhishan station
Zhishan station is a metro station on the Taipei Metro system in Taipei, Taiwan.
|
E1325240
|
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: Zhishan station | Statement: [Tamsui–Xinyi line, hasStation, Zhishan station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zhishan station Context triple: [Tamsui–Xinyi line, hasStation, Zhishan station]
-
A.
Zhichunlu station
Zhichunlu station is a subway station in Beijing that serves as part of the city's extensive urban rail transit network.
-
B.
Zhuwei station
Zhuwei station is a metro station in New Taipei, Taiwan, serving passengers on Taipei Metro’s Tamsui–Xinyi line.
-
C.
Jiantan Station
Jiantan Station is a Taipei Metro station in Taiwan that serves as a major access point for visitors to the popular Shilin Night Market.
-
D.
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.
-
E.
Jiangtai Station
Jiangtai Station is a Beijing Subway station that serves as a key access point to the nearby 798 Art Zone and surrounding Chaoyang District areas.
- 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: Zhishan station Triple: [Tamsui–Xinyi line, hasStation, Zhishan station]
Generated description
Zhishan station is a metro station on the Taipei Metro system in Taipei, Taiwan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zhishan station Target entity description: Zhishan station is a metro station on the Taipei Metro system in Taipei, Taiwan.
-
A.
Zhichunlu station
Zhichunlu station is a subway station in Beijing that serves as part of the city's extensive urban rail transit network.
-
B.
Zhuwei station
Zhuwei station is a metro station in New Taipei, Taiwan, serving passengers on Taipei Metro’s Tamsui–Xinyi line.
-
C.
Jiantan Station
Jiantan Station is a Taipei Metro station in Taiwan that serves as a major access point for visitors to the popular Shilin Night Market.
-
D.
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.
-
E.
Jiangtai Station
Jiangtai Station is a Beijing Subway station that serves as a key access point to the nearby 798 Art Zone and surrounding Chaoyang District areas.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2020342988190add65c784b8ee179 |
completed | April 17, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a040fc34f4c8190a1ae536e544b2543 |
completed | May 13, 2026, 5:44 a.m. |
| NEDg | Description generation | batch_6a04123430308190af22a11b2151c8b8 |
completed | May 13, 2026, 5:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a04131eb4988190af4024bfcad648bc |
completed | May 13, 2026, 5:58 a.m. |
Created at: April 10, 2026, 5 a.m.