Triple
T2176904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | O-Train |
E48549
|
entity |
| Predicate | branding |
P1500
|
FINISHED |
| Object | O-Train |
E48549
|
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: O-Train | Statement: [O-Train, branding, O-Train]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: O-Train Context triple: [O-Train, branding, O-Train]
-
A.
O-Train
chosen
The O-Train is Ottawa’s urban rail transit system, providing light rail service across key corridors of Canada’s capital city.
-
B.
M train
The M train is a New York City Subway service that runs through parts of Queens, Brooklyn, and Manhattan, connecting neighborhoods such as Middle Village and Forest Hills with Midtown and Lower Manhattan.
-
C.
E train
The E train is a New York City Subway service that runs primarily along the IND Eighth Avenue Line, providing rapid transit between Queens and Manhattan.
-
D.
L train
The L train is a New York City Subway service that runs crosstown along 14th Street in Manhattan and through Williamsburg and Bushwick in Brooklyn, known for its heavy ridership and role as a key connector between the boroughs.
-
E.
AeroTrain
AeroTrain is an automated underground people mover system that transports passengers between terminals at Washington Dulles International Airport.
- 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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbeecdbc881909982a58568f0b1ed |
completed | March 7, 2026, 6 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae5da14e3881909f0beda339599938 |
completed | March 9, 2026, 5:41 a.m. |
Created at: March 4, 2026, 7:45 p.m.