Triple
T1114498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UPY |
E11065
|
entity |
| Predicate | railroadCodeType |
P18202
|
FINISHED |
| Object | locomotive reporting mark |
—
|
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 reporting mark | Statement: [UPY, railroadCodeType, locomotive reporting mark]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railroadCodeType Context triple: [UPY, railroadCodeType, locomotive reporting mark]
-
A.
railroadCodeFor
chosen
Indicates that a specific railroad code is assigned to or used to identify a particular railroad entity.
-
B.
railroadClass
Indicates the classification or category of a railroad according to an established system (e.g., by size, revenue, or regulatory status).
-
C.
railSystemType
Indicates the specific category or classification of a rail transportation system that an entity belongs to or operates within.
-
D.
railServiceType
Indicates the specific category or type of rail service that applies to the relationship between the involved entities (e.g., local, express, freight).
-
E.
railwayLineType
Indicates the specific kind or classification of a railway line associated with an entity (e.g., main line, branch line, high-speed line).
- 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_69a493252a648190ac48f8742474a5e8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bbd92a8c8190a16e55f3f739010f |
completed | March 1, 2026, 10:21 p.m. |
| PD | Predicate disambiguation | batch_69a4bb42990c819080db96478fd4977e |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:43 p.m.