Triple
T930080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | InterCity |
E20070
|
entity |
| Predicate | typicalRollingStockType |
P1305
|
FINISHED |
| Object | locomotive-hauled coaches |
—
|
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: locomotive-hauled coaches | Statement: [InterCity, typicalRollingStockType, locomotive-hauled coaches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalRollingStockType Context triple: [InterCity, typicalRollingStockType, locomotive-hauled coaches]
-
A.
rollingStockType
chosen
Indicates the specific category or type of railway rolling stock associated with an entity (e.g., locomotive, passenger car, freight wagon).
-
B.
usesRollingStock
Indicates that one entity employs or operates specific rolling stock (such as rail vehicles) in its activities or services.
-
C.
introducedRollingStock
Indicates that an entity caused new rolling stock (such as trains or rail vehicles) to be put into service or use.
-
D.
railwayCarriageUsedFor
Indicates that a railway carriage is employed or designated for a particular purpose, function, or type of use.
-
E.
railSystemType
Indicates the specific category or classification of a rail transportation system that an entity belongs to or operates within.
- 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_69a493af3dc48190adb7263e6e445ea1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b349b3d0819090c58b4fb60c6a1b |
completed | March 1, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69a4b29876348190a29f4ff9878074a5 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.