Triple
T20082681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EMD GP series |
E500041
|
entity |
| Predicate | manufacturer |
P490
|
FINISHED |
| Object | Progress Rail |
—
|
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: Progress Rail | Statement: [EMD GP series, manufacturer, Progress Rail]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Progress Rail Context triple: [EMD GP series, manufacturer, Progress Rail]
-
A.
Progress Rail
chosen
Progress Rail is a major North American provider of railroad and transit products and services, including locomotive manufacturing, railcar repair, and track infrastructure solutions.
-
B.
Progress Station
Progress Station is a Russian research base in Antarctica used for scientific studies and logistical support in the region.
-
C.
Rapid Rail
Rapid Rail is a Malaysian public transport operator responsible for running several urban rail transit lines in the Greater Kuala Lumpur area.
-
D.
Peak Rail
Peak Rail is a preserved heritage railway in Derbyshire, England, operating tourist and enthusiast train services on a section of the former Midland Railway route through the Peak District.
-
E.
AutoTrain
AutoTrain is a Hugging Face platform that automates the training, tuning, and deployment of machine learning models with minimal user configuration.
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6655946f48190a6b4cb13ea4e212a |
completed | April 20, 2026, 5:41 p.m. |
Created at: April 11, 2026, 3:41 p.m.