Triple
T6650961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaohsiung MRT Orange Line |
E150818
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Daliao Station |
E609812
|
NE FINISHED |
How this triple was built (2 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: Daliao Station | Statement: [Kaohsiung MRT Orange Line, hasStation, Daliao Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daliao Station Context triple: [Kaohsiung MRT Orange Line, hasStation, Daliao Station]
-
A.
Daliao Station
chosen
Daliao Station is a metro station in Kaohsiung, Taiwan, serving as the eastern endpoint of the Kaohsiung MRT Orange Line.
-
B.
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.
-
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.
Tuqiao Station
Tuqiao Station is a subway station on Beijing's Batong Line serving the eastern suburbs of the city.
-
E.
Laojie station
Laojie station is a major interchange and one of the busiest metro stations in Shenzhen, China, serving the city’s central commercial and shopping districts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c687f2c9508190a60b9aad31d3f358 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b0458fb48190a76d8d1d6273a92b |
completed | March 27, 2026, 4:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c723b575a08190a3e0b1f233c36ba0 |
completed | March 28, 2026, 12:41 a.m. |
Created at: March 27, 2026, 2:01 p.m.