Triple
T16938615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alabama Great Southern Railroad |
E410889
|
entity |
| Predicate | railTransportType |
P21523
|
FINISHED |
| Object | freight rail |
—
|
LITERAL 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: freight rail | Statement: [Alabama Great Southern Railroad, railTransportType, freight rail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railTransportType Context triple: [Alabama Great Southern Railroad, railTransportType, freight rail]
-
A.
trainTypeUsed
Indicates that a specific type or category of train is employed or operated in a given context or service.
-
B.
rollingStockType
Indicates the specific category or type of railway rolling stock associated with an entity (e.g., locomotive, passenger car, freight wagon).
-
C.
railSystemType
Indicates the specific category or classification of a rail transportation system that an entity belongs to or operates within.
-
D.
railServiceType
chosen
Indicates the specific category or type of rail service that applies to the relationship between the involved entities (e.g., local, express, freight).
-
E.
trainsCategory
Indicates that one entity is a category or type under which the other entity is trained or classified.
- F. None of above.
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_69d886c886688190967be07322597ac9 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cf2b88bc8190aeb7b07032478ae3 |
completed | April 18, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69e32b9aa8748190b248890aca86753d |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:31 a.m.