Triple
T22398129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Esplanade MRT station |
E553689
|
entity |
| Predicate | servedByLine |
P1293
|
FINISHED |
| Object | Circle Line |
—
|
NE NERFINISHED |
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: Circle Line | Statement: [Esplanade MRT station, servedByLine, Circle Line]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Circle Line Context triple: [Esplanade MRT station, servedByLine, Circle Line]
-
A.
Circle Line
chosen
Circle Line is a mass rapid transit line in Singapore that forms a loop connecting key residential, commercial, and educational districts around the city.
-
B.
Circle Line
Circle Line is the alternative name for Seoul Subway Line 2, a major loop line encircling central Seoul and serving as one of the city's busiest metro routes.
-
C.
Circle line
The Circle line is a central London Underground route forming a loop through key districts and interchanges in the city’s transport network.
-
D.
Circular line
The Circular line is a driverless rapid transit line in the Taipei Metro system that forms a loop connecting multiple districts around the city.
-
E.
Circular line
Circular line is the nickname for Line 6 of the Madrid Metro, a heavily used underground route that forms a loop around central Madrid.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e4da7048190b4387d422a9a0de5 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15861ac248190a967f534feea0265 |
completed | April 29, 2026, 1:01 a.m. |
Created at: April 16, 2026, 8:46 p.m.