Triple
T15645489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhonghe–Xinlu line |
E376165
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object |
Huilong station
Huilong station is a metro station in New Taipei, Taiwan, serving as a key terminal stop on the Taipei Metro network.
|
E1260075
|
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: Huilong station | Statement: [Zhonghe–Xinlu line, terminus, Huilong station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Huilong station Context triple: [Zhonghe–Xinlu line, terminus, Huilong station]
-
A.
Huoying station
Huoying station is an interchange stop on the Beijing Subway that connects passengers to Line 13 and other transit services in the northern part of the city.
-
B.
Luyuan station
Luyuan station is a subway station on Beijing's Line 8 serving passengers in the city's urban transit network.
-
C.
Liyuan Station
Liyuan Station is a stop on Beijing's Batong Line serving the eastern suburbs of the city.
-
D.
Tiantongyuan station
Tiantongyuan station is a subway station in Beijing, China, serving the northern residential area of Tiantongyuan on the city's metro network.
-
E.
Wanshengwei Station
Wanshengwei Station is a metro station in Guangzhou, China, serving as a transport hub within the Guangzhou 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: Huilong station Triple: [Zhonghe–Xinlu line, terminus, Huilong station]
Generated description
Huilong station is a metro station in New Taipei, Taiwan, serving as a key terminal stop on the Taipei Metro network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Huilong station Target entity description: Huilong station is a metro station in New Taipei, Taiwan, serving as a key terminal stop on the Taipei Metro network.
-
A.
Huoying station
Huoying station is an interchange stop on the Beijing Subway that connects passengers to Line 13 and other transit services in the northern part of the city.
-
B.
Luyuan station
Luyuan station is a subway station on Beijing's Line 8 serving passengers in the city's urban transit network.
-
C.
Liyuan Station
Liyuan Station is a stop on Beijing's Batong Line serving the eastern suburbs of the city.
-
D.
Tiantongyuan station
Tiantongyuan station is a subway station in Beijing, China, serving the northern residential area of Tiantongyuan on the city's metro network.
-
E.
Wanshengwei Station
Wanshengwei Station is a metro station in Guangzhou, China, serving as a transport hub within the Guangzhou 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed5b8b081908d7127964eed3b09 |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01792dc0b08190a0871959ce752313 |
completed | May 11, 2026, 6:37 a.m. |
| NEDg | Description generation | batch_6a0179f16af481909f409adb5367f021 |
completed | May 11, 2026, 6:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a017ad8480881909ca9a9982585b08d |
completed | May 11, 2026, 6:44 a.m. |
Created at: April 10, 2026, 4:15 a.m.