Triple
T2470159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JR-O11 |
E55350
|
entity |
| Predicate | railwayLineSystem |
P522
|
FINISHED |
| Object | Osaka Loop Line station numbering 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: Osaka Loop Line station numbering system | Statement: [JR-O11, railwayLineSystem, Osaka Loop Line station numbering system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railwayLineSystem Context triple: [JR-O11, railwayLineSystem, Osaka Loop Line station numbering system]
-
A.
railwayLine
Indicates that there is a railway line connection or route associated with or passing through the referenced entity.
-
B.
railroadNetwork
Indicates a relationship where locations are connected as part of the same system of railway lines and infrastructure used for train transport.
-
C.
railwayLineType
Indicates the specific kind or classification of a railway line associated with an entity (e.g., main line, branch line, high-speed line).
-
D.
hasRailSystem
chosen
Indicates that an entity possesses or is served by a rail-based transportation system.
-
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_69ab49e3622c8190ad22afa2c4fbb807 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd2bc7b5481908b3664495e99f1a4 |
completed | March 7, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69abd0b3ea308190a6d8499c2a542c50 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:44 p.m.