Triple
T11329820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sentosa Express |
E268311
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Waterfront station |
E276150
|
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: Waterfront station | Statement: [Sentosa Express, hasStation, Waterfront station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waterfront station Context triple: [Sentosa Express, hasStation, Waterfront station]
-
A.
Waterfront station
Waterfront station is a Washington Metro rapid transit stop in Southwest Washington, D.C., serving the Green Line and the surrounding waterfront neighborhood.
-
B.
Waterfront Station
chosen
Waterfront Station is a major transit hub in downtown Vancouver, British Columbia, serving multiple rail and bus lines and providing access to the historic Gastown district.
-
C.
Riverside station
Riverside station is a major Massachusetts Bay Transportation Authority light rail station and park-and-ride hub located in Newton, Massachusetts.
-
D.
Bayside station
Bayside station is a Long Island Rail Road commuter rail stop in the Bayside neighborhood of Queens, New York City.
-
E.
Terminal Station
Terminal Station is a passenger stop on Detroit Metropolitan Airport’s McNamara Terminal ExpressTram automated people mover system.
- 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_69d6aacb1f0881908c84a349fd1be047 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9e330008190b75490efde01dc59 |
completed | April 9, 2026, 6:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e526236b688190aca4f2400a12e726 |
completed | April 19, 2026, 6:59 p.m. |
Created at: April 8, 2026, 9:32 p.m.