Triple
T16198367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 38th Street Station |
E393127
|
entity |
| Predicate | partOfSystem |
P840
|
FINISHED |
| Object | METRO light rail |
E56106
|
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: METRO light rail | Statement: [38th Street Station, partOfSystem, METRO light rail]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: METRO light rail Context triple: [38th Street Station, partOfSystem, METRO light rail]
-
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.
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.
-
C.
MAX Light Rail
MAX Light Rail is the metropolitan light rail transit system serving the Portland, Oregon, metropolitan 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 (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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e222dc6b1c8190a3d8a6451ed8b95a |
completed | April 17, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00078db04081909f7e14b09687ba67 |
completed | May 10, 2026, 4:20 a.m. |
Created at: April 10, 2026, 5:03 a.m.