Triple
T1114491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UPY |
E11065
|
entity |
| Predicate | markingSystem |
P6736
|
FINISHED |
| Object | North American railroad reporting mark system |
—
|
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: North American railroad reporting mark system | Statement: [UPY, markingSystem, North American railroad reporting mark system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: markingSystem Context triple: [UPY, markingSystem, North American railroad reporting mark system]
-
A.
marks
Indicates that one entity makes a visible or symbolic sign on, or designates, another entity for identification, emphasis, or distinction.
-
B.
markType
Indicates the specific category or kind of mark associated with or applied to an entity.
-
C.
scoring
Indicates the act of achieving points or a measurable result, typically by successfully completing an action that contributes to a score or outcome.
-
D.
ratingSystem
Indicates a system or method used to assign evaluative scores or rankings to items, actions, or entities based on defined criteria.
-
E.
classificationSystem
chosen
Indicates a relationship where an entity is organized or categorized according to a particular classification scheme or taxonomy.
- 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.