Triple
T12719331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bang Wa Station |
E303932
|
entity |
| Predicate | isInterchangeBetween |
P21487
|
FINISHED |
| Object | MRT Blue Line |
E300207
|
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: MRT Blue Line | Statement: [Bang Wa Station, isInterchangeBetween, MRT Blue Line]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MRT Blue Line Context triple: [Bang Wa Station, isInterchangeBetween, MRT Blue Line]
-
A.
MRT Blue Line
chosen
The MRT Blue Line is a major rapid transit route in Bangkok’s Metropolitan Rapid Transit system, serving as one of the city’s primary underground and elevated rail corridors.
-
B.
MRT Orange Line
The MRT Orange Line is a rapid transit route in Bangkok’s Mass Rapid Transit system designed to connect key eastern and western parts of the city.
-
C.
MRT Yellow Line
MRT Yellow Line is a mass rapid transit route typically designated by the color yellow, serving as one of the lines in an urban MRT subway network.
-
D.
MRT Brown Line
The MRT Brown Line is a mass rapid transit route in Singapore that serves as part of the city’s urban subway network.
-
E.
MRT Purple Line
The MRT Purple Line is a mass rapid transit route in Bangkok, Thailand, serving as one of the city's key urban rail corridors.
- 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_69d7bdf084148190ab9d513dc0735af4 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96411d87481909127e81755f23964 |
completed | April 10, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6fef8d94081908ea5ac426e22ef87 |
completed | May 3, 2026, 7:53 a.m. |
Created at: April 9, 2026, 5:24 p.m.