Triple
T19720583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Line (METRORail) |
E473596
|
entity |
| Predicate | system |
P730
|
FINISHED |
| Object | METRORail |
—
|
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: METRORail | Statement: [Green Line (METRORail), system, METRORail]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: METRORail Context triple: [Green Line (METRORail), system, METRORail]
-
A.
Metro Rail
Metro Rail is the light rail rapid transit system serving the Buffalo–Niagara region of New York.
-
B.
Metro Rail
Metro Rail is the urban rapid transit rail system serving Los Angeles County, providing light rail and subway services across the region.
-
C.
METRORail light rail
chosen
METRORail light rail is Houston's urban light rail transit system operated by METRO, connecting key destinations throughout the city’s central area.
-
D.
Metrorail
Metrorail is the rapid transit system serving the Washington, D.C. metropolitan area, operated by the Washington Metropolitan Area Transit Authority (WMATA).
-
E.
Metrorail
Metrorail is a South African commuter rail service that operates urban and suburban passenger trains in major metropolitan areas across the country.
- 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_69d8e516dd048190a0b6c93ea3e71f58 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e649f483c481908c6b3114bf9c5934 |
completed | April 20, 2026, 3:44 p.m. |
Created at: April 10, 2026, 1:46 p.m.