Triple
T5035909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benning |
E113420
|
entity |
| Predicate | hasPublicTransit |
P522
|
FINISHED |
| Object | Metrorail |
E56829
|
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: Metrorail | Statement: [Benning, hasPublicTransit, Metrorail]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Metrorail Context triple: [Benning, hasPublicTransit, Metrorail]
-
A.
Metrorail
Metrorail is Miami-Dade County’s elevated rapid transit system that connects key neighborhoods, suburbs, and downtown Miami.
-
B.
Metrorail
chosen
Metrorail is the rapid transit system serving the Washington, D.C. metropolitan area, operated by the Washington Metropolitan Area Transit Authority (WMATA).
-
C.
Metro Rail
Metro Rail is the urban rapid transit rail system serving Los Angeles County, providing light rail and subway services across the region.
-
D.
METRORail Red Line
The METRORail Red Line is a light rail line in Houston, Texas, running through key central areas including downtown and the Museum District.
-
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_69bd44384298819089c49e7c330ec7b8 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd73b9ad488190a2a8c4da8858eb91 |
completed | March 20, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be9c79265081908512b39cc74161f8 |
completed | March 21, 2026, 1:26 p.m. |
Created at: March 20, 2026, 1:36 p.m.