Triple
T15476457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taoyuan Airport MRT |
E376791
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Dayuan Station
Dayuan Station is a metro station in Taoyuan, Taiwan, serving passengers on the Taoyuan Airport MRT line between central Taoyuan and Taiwan Taoyuan International Airport.
|
E1205381
|
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: Dayuan Station | Statement: [Taoyuan Airport MRT, hasStation, Dayuan Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dayuan Station Context triple: [Taoyuan Airport MRT, hasStation, Dayuan Station]
-
A.
Daliao Station
Daliao Station is a metro station in Kaohsiung, Taiwan, serving as the eastern endpoint of the Kaohsiung MRT Orange Line.
-
B.
Tuqiao Station
Tuqiao Station is a subway station on Beijing's Batong Line serving the eastern suburbs of the city.
-
C.
Liyuan Station
Liyuan Station is a stop on Beijing's Batong Line serving the eastern suburbs of the city.
-
D.
Huanbei Station
Huanbei Station is a metro station in Taoyuan, Taiwan, serving as one end of the Taoyuan Airport MRT line and providing access to the surrounding urban area.
-
E.
Lijiao Station
Lijiao Station is an interchange station on the Guangzhou Metro system in Guangzhou, China, serving as a local transit hub for passengers in its surrounding urban area.
- 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: Dayuan Station Triple: [Taoyuan Airport MRT, hasStation, Dayuan Station]
Generated description
Dayuan Station is a metro station in Taoyuan, Taiwan, serving passengers on the Taoyuan Airport MRT line between central Taoyuan and Taiwan Taoyuan International Airport.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dayuan Station Target entity description: Dayuan Station is a metro station in Taoyuan, Taiwan, serving passengers on the Taoyuan Airport MRT line between central Taoyuan and Taiwan Taoyuan International Airport.
-
A.
Daliao Station
Daliao Station is a metro station in Kaohsiung, Taiwan, serving as the eastern endpoint of the Kaohsiung MRT Orange Line.
-
B.
Tuqiao Station
Tuqiao Station is a subway station on Beijing's Batong Line serving the eastern suburbs of the city.
-
C.
Liyuan Station
Liyuan Station is a stop on Beijing's Batong Line serving the eastern suburbs of the city.
-
D.
Huanbei Station
Huanbei Station is a metro station in Taoyuan, Taiwan, serving as one end of the Taoyuan Airport MRT line and providing access to the surrounding urban area.
-
E.
Lijiao Station
Lijiao Station is an interchange station on the Guangzhou Metro system in Guangzhou, China, serving as a local transit hub for passengers in its surrounding urban area.
- 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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f88a5dc8190a2d7830748e29180 |
completed | April 16, 2026, 1:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001f7d79348190aba1889a7eb3d7c8 |
completed | May 10, 2026, 6:02 a.m. |
| NEDg | Description generation | batch_6a0020ffeca88190bd983923f2cc1522 |
completed | May 10, 2026, 6:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00219a089c81909bb4f442cb26930d |
completed | May 10, 2026, 6:11 a.m. |
Created at: April 10, 2026, 3:34 a.m.