Triple
T6524447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Transitway |
E151266
|
entity |
| Predicate | integratedWith |
P2830
|
FINISHED |
| Object | O-Train light rail system |
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 light rail system | Statement: [Transitway, integratedWith, O-Train light rail system]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: O-Train light rail system Context triple: [Transitway, integratedWith, O-Train light rail system]
-
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.
LYNX light rail system
The LYNX light rail system is Charlotte, North Carolina’s urban rail transit network, providing electric passenger service along key corridors such as the Blue Line.
-
C.
MAX Light Rail
MAX Light Rail is the metropolitan light rail transit system serving the Portland, Oregon, metropolitan area.
-
D.
DART Light Rail
DART Light Rail is a light rail transit system serving the Dallas–Fort Worth metropolitan area, operated by Dallas Area Rapid Transit.
-
E.
METRO light rail
METRO light rail is a rapid transit system serving the Minneapolis–Saint Paul metropolitan area with multiple color-designated lines connecting key urban, suburban, and airport destinations.
- 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_69c687f522748190b3058405553cdabd |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ad9831f88190a2b64cf6bc8c9a11 |
completed | March 27, 2026, 4:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6f7813a788190a25ace732cf4e3d0 |
completed | March 27, 2026, 9:32 p.m. |
Created at: March 27, 2026, 1:45 p.m.