Triple
T20008100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victoria Street Station |
E494511
|
entity |
| Predicate | partOfNetwork |
P840
|
FINISHED |
| Object | METRO light rail system |
—
|
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: METRO light rail system | Statement: [Victoria Street Station, partOfNetwork, METRO light rail system]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: METRO light rail system Context triple: [Victoria Street Station, partOfNetwork, METRO light rail system]
-
A.
METRO light rail
chosen
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.
-
B.
MAX Light Rail
MAX Light Rail is the metropolitan light rail transit system serving the Portland, Oregon, metropolitan area.
-
C.
METRORail light rail
METRORail light rail is Houston's urban light rail transit system operated by METRO, connecting key destinations throughout the city’s central area.
-
D.
Metro Rail
Metro Rail is the light rail rapid transit system serving the Buffalo–Niagara region of New York.
-
E.
Metro Rail
Metro Rail is the urban rapid transit rail system serving Los Angeles County, providing light rail and subway services across the region.
- 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e661a7500481908b69f74e479f88c8 |
completed | April 20, 2026, 5:25 p.m. |
Created at: April 11, 2026, 3:33 p.m.